diff --git a/Introduction-to-Pandas--master.ipynb b/Introduction-to-Pandas--master.ipynb
index d40d3b71282802f67e55a3ce6fbf414103095743..580180d4a511817670b926f90c5003f840eaccc3 100644
--- a/Introduction-to-Pandas--master.ipynb
+++ b/Introduction-to-Pandas--master.ipynb
@@ -174,7 +174,7 @@
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@@ -187,7 +187,7 @@
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@@ -201,7 +201,7 @@
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@@ -214,7 +214,7 @@
"'1.4.2'"
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+ "execution_count": 9,
"metadata": {},
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@@ -225,7 +225,7 @@
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@@ -338,7 +338,7 @@
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@@ -351,7 +351,7 @@
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+ "execution_count": 12,
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@@ -441,7 +441,7 @@
"9 60"
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+ "execution_count": 12,
"metadata": {},
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@@ -452,7 +452,7 @@
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+ "execution_count": 13,
"metadata": {
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@@ -507,7 +507,7 @@
"2 56"
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- "execution_count": 7,
+ "execution_count": 13,
"metadata": {},
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@@ -530,7 +530,7 @@
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- "execution_count": 7,
+ "execution_count": 14,
"metadata": {
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@@ -555,7 +555,7 @@
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{
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- "execution_count": 8,
+ "execution_count": 15,
"metadata": {
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@@ -620,7 +620,7 @@
"3 Waters 57"
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- "execution_count": 8,
+ "execution_count": 15,
"metadata": {},
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@@ -644,7 +644,7 @@
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{
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- "execution_count": 9,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
@@ -653,7 +653,7 @@
"Index(['Name', 'Age'], dtype='object')"
]
},
- "execution_count": 9,
+ "execution_count": 16,
"metadata": {},
"output_type": "execute_result"
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@@ -676,7 +676,7 @@
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{
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- "execution_count": 10,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
@@ -685,7 +685,7 @@
"RangeIndex(start=0, stop=10, step=1)"
]
},
- "execution_count": 10,
+ "execution_count": 17,
"metadata": {},
"output_type": "execute_result"
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@@ -708,7 +708,7 @@
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- "execution_count": 11,
+ "execution_count": 18,
"metadata": {
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@@ -803,7 +803,7 @@
"Hall 60"
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+ "execution_count": 18,
"metadata": {},
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@@ -826,7 +826,7 @@
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- "execution_count": 12,
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@@ -906,7 +906,7 @@
"max 60.000000"
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- "execution_count": 12,
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@@ -917,7 +917,7 @@
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- "execution_count": 13,
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"metadata": {
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@@ -980,7 +980,7 @@
"Age 41 56 56 57 39 59 43 56 38 60"
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- "execution_count": 13,
+ "execution_count": 20,
"metadata": {},
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@@ -991,7 +991,7 @@
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@@ -1006,7 +1006,7 @@
" dtype='object', name='Name')"
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- "execution_count": 14,
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@@ -1028,7 +1028,7 @@
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@@ -1088,7 +1088,7 @@
"Rivers 112"
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- "execution_count": 15,
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@@ -1099,7 +1099,7 @@
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- "execution_count": 16,
+ "execution_count": 23,
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@@ -1158,7 +1158,7 @@
"2 RiversRivers 112"
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@@ -1169,7 +1169,7 @@
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@@ -1229,7 +1229,7 @@
"Rivers 28.0"
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@@ -1240,7 +1240,7 @@
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- "execution_count": 18,
+ "execution_count": 25,
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@@ -1300,7 +1300,7 @@
"Rivers 3136"
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@@ -1311,7 +1311,7 @@
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- "execution_count": 19,
+ "execution_count": 26,
"metadata": {
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@@ -1382,7 +1382,7 @@
"Rice 1521"
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- "execution_count": 19,
+ "execution_count": 26,
"metadata": {},
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@@ -1397,7 +1397,7 @@
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@@ -1410,7 +1410,7 @@
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@@ -1481,7 +1481,7 @@
"Rice 1521"
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- "execution_count": 21,
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"metadata": {},
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@@ -1504,7 +1504,7 @@
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- "execution_count": 22,
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"metadata": {
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@@ -1597,7 +1597,7 @@
"Hall True"
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- "execution_count": 22,
+ "execution_count": 29,
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@@ -1608,7 +1608,7 @@
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- "execution_count": 23,
+ "execution_count": 30,
"metadata": {
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@@ -1679,7 +1679,7 @@
"Rice True"
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- "execution_count": 23,
+ "execution_count": 30,
"metadata": {},
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@@ -1727,7 +1727,7 @@
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- "execution_count": 24,
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"metadata": {
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@@ -1746,7 +1746,7 @@
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{
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- "execution_count": 25,
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"metadata": {
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@@ -1816,7 +1816,7 @@
"Favourite Color violet gray "
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- "execution_count": 25,
+ "execution_count": 32,
"metadata": {},
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@@ -1844,7 +1844,7 @@
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- "execution_count": 26,
+ "execution_count": 33,
"metadata": {},
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{
@@ -1929,7 +1929,7 @@
"4 1.2 2018-02-26 -0.718282 entries Same"
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- "execution_count": 26,
+ "execution_count": 33,
"metadata": {},
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@@ -1947,7 +1947,7 @@
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- "execution_count": 27,
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"metadata": {
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@@ -2036,7 +2036,7 @@
"1 1.2 2018-02-26 1.718282 column Same"
]
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- "execution_count": 27,
+ "execution_count": 34,
"metadata": {},
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@@ -2047,7 +2047,7 @@
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{
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- "execution_count": 28,
+ "execution_count": 35,
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@@ -2109,7 +2109,7 @@
"4 1.2 2018-02-26 -0.72 entries Same"
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},
- "execution_count": 28,
+ "execution_count": 35,
"metadata": {},
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@@ -2120,7 +2120,7 @@
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{
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- "execution_count": 31,
+ "execution_count": 36,
"metadata": {
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@@ -2131,7 +2131,7 @@
"name": "stderr",
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"text": [
- "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/1325867503.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n",
+ "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/1325867503.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n",
" df_demo.round(2).sum()\n"
]
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@@ -2144,7 +2144,7 @@
"dtype: object"
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- "execution_count": 31,
+ "execution_count": 36,
"metadata": {},
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@@ -2155,7 +2155,7 @@
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{
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- "execution_count": 32,
+ "execution_count": 37,
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@@ -2184,7 +2184,7 @@
"name": "stderr",
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- "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/3396683912.py:1: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
+ "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/3396683912.py:1: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
" print(df_demo.round(2).to_latex())\n"
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@@ -2222,7 +2222,7 @@
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- "execution_count": 33,
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@@ -2305,7 +2305,7 @@
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- "execution_count": 33,
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@@ -2335,7 +2335,7 @@
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@@ -2363,7 +2363,7 @@
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@@ -2587,7 +2587,7 @@
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- "execution_count": 35,
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@@ -2657,7 +2657,7 @@
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@@ -2724,7 +2724,7 @@
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- "execution_count": 36,
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@@ -2735,7 +2735,7 @@
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@@ -2754,7 +2754,7 @@
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@@ -2777,7 +2777,7 @@
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- "execution_count": 38,
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@@ -2793,7 +2793,7 @@
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@@ -2824,7 +2824,7 @@
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- "execution_count": 39,
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@@ -2895,7 +2895,7 @@
"4 1.2 -0.718282"
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- "execution_count": 39,
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@@ -2919,7 +2919,7 @@
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+ "execution_count": 45,
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{
@@ -2977,7 +2977,7 @@
"2 1.2 2018-02-26 -1.304068 has Same"
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- "execution_count": 40,
+ "execution_count": 45,
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@@ -2988,7 +2988,7 @@
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- "execution_count": 41,
+ "execution_count": 46,
"metadata": {
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@@ -3051,7 +3051,7 @@
"3 1.2 2018-02-26 0.986231 entries Same"
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- "execution_count": 41,
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@@ -3073,7 +3073,7 @@
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+ "execution_count": 47,
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@@ -3131,7 +3131,7 @@
"2 1.2 2018-02-26 -1.304068 has Same"
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- "execution_count": 42,
+ "execution_count": 47,
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@@ -3142,7 +3142,7 @@
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@@ -3200,7 +3200,7 @@
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- "execution_count": 43,
+ "execution_count": 48,
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@@ -3227,7 +3227,7 @@
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"metadata": {
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@@ -3287,7 +3287,7 @@
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- "execution_count": 44,
+ "execution_count": 49,
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@@ -3310,7 +3310,7 @@
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+ "execution_count": 50,
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@@ -3359,7 +3359,7 @@
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- "execution_count": 45,
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@@ -3383,7 +3383,7 @@
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+ "execution_count": 51,
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@@ -3474,7 +3474,7 @@
"entries 1.2 2018-02-26 -0.718282 Same"
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- "execution_count": 46,
+ "execution_count": 51,
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@@ -3486,7 +3486,7 @@
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+ "execution_count": 52,
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@@ -3549,7 +3549,7 @@
"entries 1.2 2018-02-26 -0.718282 Same"
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- "execution_count": 47,
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@@ -3560,7 +3560,7 @@
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@@ -3626,7 +3626,7 @@
"entries 1.2 -0.718282"
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- "execution_count": 48,
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@@ -3656,7 +3656,7 @@
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@@ -3714,7 +3714,7 @@
"3 1.2 2018-02-26 0.986231 entries Same"
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@@ -3725,7 +3725,7 @@
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+ "execution_count": 55,
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@@ -3739,7 +3739,7 @@
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- "execution_count": 50,
+ "execution_count": 55,
"metadata": {},
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@@ -3750,7 +3750,7 @@
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{
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- "execution_count": 51,
+ "execution_count": 56,
"metadata": {
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@@ -3803,7 +3803,7 @@
"4 1.2 2018-02-26 -0.718282 entries Same"
]
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- "execution_count": 51,
+ "execution_count": 56,
"metadata": {},
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@@ -3833,7 +3833,7 @@
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{
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- "execution_count": 52,
+ "execution_count": 57,
"metadata": {
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@@ -3904,7 +3904,7 @@
"2 1.2 2018-02-26 -1.304068 has Same"
]
},
- "execution_count": 52,
+ "execution_count": 57,
"metadata": {},
"output_type": "execute_result"
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@@ -3915,7 +3915,7 @@
},
{
"cell_type": "code",
- "execution_count": 53,
+ "execution_count": 58,
"metadata": {
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@@ -3991,7 +3991,7 @@
"2 1.2 2018-02-26 -1.304068 has Same -2.504068"
]
},
- "execution_count": 53,
+ "execution_count": 58,
"metadata": {},
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@@ -4016,7 +4016,7 @@
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{
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- "execution_count": 54,
+ "execution_count": 59,
"metadata": {
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@@ -4096,7 +4096,7 @@
"2 1.2 2018-02-26 -1.304068 has Same 1.700594 -2.504068"
]
},
- "execution_count": 54,
+ "execution_count": 59,
"metadata": {},
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@@ -4108,11 +4108,16 @@
},
{
"cell_type": "code",
- "execution_count": 55,
+ "execution_count": 60,
"metadata": {
+ "collapsed": true,
+ "jupyter": {
+ "outputs_hidden": true
+ },
"slideshow": {
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- }
+ },
+ "tags": []
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"outputs": [
{
@@ -4187,7 +4192,7 @@
"4 1.2 2018-02-26 -0.718282 entries Same 0.515929 -1.918282"
]
},
- "execution_count": 55,
+ "execution_count": 60,
"metadata": {},
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@@ -4198,18 +4203,19 @@
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+ "execution_count": 69,
"metadata": {
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- }
+ "slide_type": "subslide"
+ },
+ "tags": []
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"text": [
- "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/2974913581.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
+ "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/363555535.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
" df_demo.append(\n"
]
},
@@ -4318,7 +4324,7 @@
"5 1.3 2018-02-27 -0.777000 has it? Same NaN 23.000000"
]
},
- "execution_count": 63,
+ "execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
@@ -4327,7 +4333,27 @@
"df_demo.append(\n",
" {\"A\": 1.3, \"B\": pd.Timestamp(\"2018-02-27\"), \"C\": -0.777, \"D\": \"has it?\", \"E\": \"Same\", \"F\": 23},\n",
" ignore_index=True\n",
- ") # TODO: Fix me"
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "slideshow": {
+ "slide_type": "fragment"
+ },
+ "tags": []
+ },
+ "source": [
+ "`.append()` seems to be deprecated; one needs to use something like the following in thef future:\n",
+ "```python\n",
+ "pd.concat(\n",
+ " [\n",
+ " df_demo, \n",
+ " pd.DataFrame({\"A\": 1.3, \"B\": pd.Timestamp(\"2018-02-27\"), \"C\": -0.777, \"D\": \"has it?\", \"E\": \"Same\", \"F\": 23}, index=[0])\n",
+ " ], ignore_index=True\n",
+ ")\n",
+ "```"
]
},
{
@@ -7322,10 +7348,10 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.2"
+ "version": "3.10.4"
},
"toc-autonumbering": false,
- "toc-showcode": true,
+ "toc-showcode": false,
"toc-showmarkdowntxt": false,
"toc-showtags": true
},
diff --git a/Introduction-to-Pandas--slides.html b/Introduction-to-Pandas--slides.html
index b34a4ab7f5ba25c8d3b639b449e87c0a62605e18..c29907e8ae5b8711833abe1f36a9339d101c79fb 100644
--- a/Introduction-to-Pandas--slides.html
+++ b/Introduction-to-Pandas--slides.html
@@ -14800,7 +14800,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
@@ -14832,7 +14832,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pd</span><span class="o">.</span><span class="n">__version__</span>
@@ -14853,7 +14853,7 @@ div.jp-OutputPrompt {
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@@ -14873,7 +14873,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%</span><span class="k">pdoc</span> pd
@@ -15005,7 +15005,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ages</span> <span class="o">=</span> <span class="p">[</span><span class="mi">41</span><span class="p">,</span> <span class="mi">56</span><span class="p">,</span> <span class="mi">56</span><span class="p">,</span> <span class="mi">57</span><span class="p">,</span> <span class="mi">39</span><span class="p">,</span> <span class="mi">59</span><span class="p">,</span> <span class="mi">43</span><span class="p">,</span> <span class="mi">56</span><span class="p">,</span> <span class="mi">38</span><span class="p">,</span> <span class="mi">60</span><span class="p">]</span>
@@ -15021,7 +15021,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">ages</span><span class="p">)</span>
@@ -15042,7 +15042,7 @@ div.jp-OutputPrompt {
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- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[6]:</div>
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@@ -15125,7 +15125,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_ages</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">ages</span><span class="p">)</span>
@@ -15147,7 +15147,7 @@ div.jp-OutputPrompt {
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@@ -15216,7 +15216,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data</span> <span class="o">=</span> <span class="p">{</span>
@@ -15259,7 +15259,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
@@ -15281,7 +15281,7 @@ div.jp-OutputPrompt {
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@@ -15360,7 +15360,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span><span class="o">.</span><span class="n">index</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s2">"Name"</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
@@ -15494,7 +15494,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
@@ -15616,7 +15616,7 @@ div.jp-OutputPrompt {
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@@ -15798,7 +15798,7 @@ div.jp-OutputPrompt {
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@@ -15834,7 +15834,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span><span class="o">.</span><span class="n">multiply</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
@@ -15855,7 +15855,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[15]:</div>
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@@ -15914,7 +15914,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span><span class="o">.</span><span class="n">multiply</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
@@ -15935,7 +15935,7 @@ div.jp-OutputPrompt {
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+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[23]:</div>
@@ -15994,7 +15994,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [17]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="p">(</span><span class="n">df_sample</span> <span class="o">/</span> <span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
@@ -16015,7 +16015,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
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+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[24]:</div>
@@ -16074,7 +16074,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
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<div class=" highlight hl-ipython3"><pre><span></span><span class="p">(</span><span class="n">df_sample</span> <span class="o">*</span> <span class="n">df_sample</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
@@ -16095,7 +16095,7 @@ div.jp-OutputPrompt {
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+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[25]:</div>
@@ -16154,7 +16154,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">mysquare</span><span class="p">(</span><span class="n">number</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
@@ -16179,7 +16179,7 @@ div.jp-OutputPrompt {
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@@ -16246,7 +16246,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">square</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
@@ -16267,7 +16267,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
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@@ -16346,7 +16346,7 @@ div.jp-OutputPrompt {
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span> <span class="o">></span> <span class="mi">40</span>
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</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [23]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [30]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_sample</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">mysquare</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">()</span> <span class="o">==</span> <span class="n">df_sample</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">*</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
@@ -16475,7 +16475,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[23]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[30]:</div>
@@ -16565,7 +16565,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [24]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [31]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">happy_dinos</span> <span class="o">=</span> <span class="p">{</span>
@@ -16586,7 +16586,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [25]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [32]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">happy_dinos</span> <span class="o">=</span> <span class="p">{</span>
@@ -16613,7 +16613,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[25]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[32]:</div>
@@ -16690,7 +16690,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [26]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [33]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span>
@@ -16718,7 +16718,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[26]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[33]:</div>
@@ -16805,7 +16805,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [27]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [34]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s2">"C"</span><span class="p">)</span>
@@ -16826,7 +16826,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[27]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[34]:</div>
@@ -16913,7 +16913,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [28]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [35]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">tail</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
@@ -16934,7 +16934,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[28]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[35]:</div>
@@ -16997,7 +16997,7 @@ div.jp-OutputPrompt {
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [31]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [36]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
@@ -17022,7 +17022,7 @@ div.jp-OutputPrompt {
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
-<pre>/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/1325867503.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.
+<pre>/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/1325867503.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.
df_demo.round(2).sum()
</pre>
</div>
@@ -17031,7 +17031,7 @@ div.jp-OutputPrompt {
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[31]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[36]:</div>
@@ -17054,7 +17054,7 @@ dtype: object</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [32]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [37]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">df_demo</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">to_latex</span><span class="p">())</span>
@@ -17102,7 +17102,7 @@ dtype: object</pre>
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
-<pre>/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/3396683912.py:1: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.
+<pre>/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/3396683912.py:1: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.
print(df_demo.round(2).to_latex())
</pre>
</div>
@@ -17142,7 +17142,7 @@ dtype: object</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [33]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [38]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pd</span><span class="o">.</span><span class="n">read_json</span><span class="p">(</span><span class="s2">"data-lost.json"</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s2">"Character"</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
@@ -17163,7 +17163,7 @@ dtype: object</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[33]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[38]:</div>
@@ -17261,7 +17261,7 @@ dtype: object</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [34]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [39]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="o">!</span>head data-nest.csv
@@ -17309,7 +17309,7 @@ dtype: object</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [35]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [40]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">"data-nest.csv"</span><span class="p">)</span>
@@ -17331,7 +17331,7 @@ dtype: object</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[35]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[40]:</div>
@@ -17577,7 +17577,7 @@ dtype: object</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [36]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [41]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
@@ -17598,7 +17598,7 @@ dtype: object</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[36]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[41]:</div>
@@ -17669,7 +17669,7 @@ dtype: object</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [37]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [42]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="p">[</span><span class="s1">'C'</span><span class="p">]</span>
@@ -17690,7 +17690,7 @@ dtype: object</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[37]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[42]:</div>
@@ -17729,7 +17729,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [38]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [43]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">C</span>
@@ -17750,7 +17750,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[38]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[43]:</div>
@@ -17805,7 +17805,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [39]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [44]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">my_slice</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'A'</span><span class="p">,</span> <span class="s1">'C'</span><span class="p">]</span>
@@ -17827,7 +17827,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[39]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[44]:</div>
@@ -17911,7 +17911,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [40]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [45]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="p">[</span><span class="mi">1</span><span class="p">:</span><span class="mi">3</span><span class="p">]</span>
@@ -17932,7 +17932,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[40]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[45]:</div>
@@ -17995,7 +17995,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [41]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [46]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="p">[</span><span class="mi">1</span><span class="p">:</span><span class="mi">6</span><span class="p">:</span><span class="mi">2</span><span class="p">]</span>
@@ -18016,7 +18016,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[41]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[46]:</div>
@@ -18093,7 +18093,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [42]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [47]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="p">[</span><span class="mi">1</span><span class="p">:</span><span class="mi">3</span><span class="p">]</span>
@@ -18114,7 +18114,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[42]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[47]:</div>
@@ -18177,7 +18177,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [43]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [48]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s2">"C"</span><span class="p">)[</span><span class="mi">1</span><span class="p">:</span><span class="mi">3</span><span class="p">]</span>
@@ -18198,7 +18198,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[43]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[48]:</div>
@@ -18275,7 +18275,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [44]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [49]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">1</span><span class="p">:</span><span class="mi">3</span><span class="p">]</span>
@@ -18296,7 +18296,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[44]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[49]:</div>
@@ -18373,7 +18373,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [45]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [50]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">1</span><span class="p">:</span><span class="mi">3</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">]]</span>
@@ -18394,7 +18394,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[45]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[50]:</div>
@@ -18464,7 +18464,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [46]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [51]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo_indexed</span> <span class="o">=</span> <span class="n">df_demo</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s2">"D"</span><span class="p">)</span>
@@ -18486,7 +18486,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[46]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[51]:</div>
@@ -18574,7 +18574,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
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-<div class="jp-InputPrompt jp-InputArea-prompt">In [47]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [52]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo_indexed</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">"entries"</span><span class="p">]</span>
@@ -18595,7 +18595,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[47]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[52]:</div>
@@ -18662,7 +18662,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [48]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [53]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo_indexed</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s2">"has"</span><span class="p">,</span> <span class="s2">"entries"</span><span class="p">],</span> <span class="p">[</span><span class="s2">"A"</span><span class="p">,</span> <span class="s2">"C"</span><span class="p">]]</span>
@@ -18683,7 +18683,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[48]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[53]:</div>
@@ -18772,7 +18772,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [49]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [54]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="p">[</span><span class="n">df_demo</span><span class="p">[</span><span class="s2">"C"</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span><span class="p">]</span>
@@ -18793,7 +18793,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[49]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[54]:</div>
@@ -18856,7 +18856,7 @@ Name: C, dtype: float64</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [50]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [55]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="p">[</span><span class="s2">"C"</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span>
@@ -18877,7 +18877,7 @@ Name: C, dtype: float64</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[50]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[55]:</div>
@@ -18902,7 +18902,7 @@ Name: C, dtype: bool</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [51]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [56]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="p">[(</span><span class="n">df_demo</span><span class="p">[</span><span class="s2">"C"</span><span class="p">]</span> <span class="o"><</span> <span class="mi">0</span><span class="p">)</span> <span class="o">&</span> <span class="p">(</span><span class="n">df_demo</span><span class="p">[</span><span class="s2">"D"</span><span class="p">]</span> <span class="o">==</span> <span class="s2">"entries"</span><span class="p">)]</span>
@@ -18923,7 +18923,7 @@ Name: C, dtype: bool</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[51]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[56]:</div>
@@ -19000,7 +19000,7 @@ Name: C, dtype: bool</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [52]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [57]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
@@ -19021,7 +19021,7 @@ Name: C, dtype: bool</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[52]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[57]:</div>
@@ -19092,7 +19092,7 @@ Name: C, dtype: bool</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [53]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [58]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="p">[</span><span class="s2">"F"</span><span class="p">]</span> <span class="o">=</span> <span class="n">df_demo</span><span class="p">[</span><span class="s2">"C"</span><span class="p">]</span> <span class="o">-</span> <span class="n">df_demo</span><span class="p">[</span><span class="s2">"A"</span><span class="p">]</span>
@@ -19114,7 +19114,7 @@ Name: C, dtype: bool</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[53]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[58]:</div>
@@ -19204,7 +19204,7 @@ Name: C, dtype: bool</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [54]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [59]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="n">df_demo</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">"E2"</span><span class="p">,</span> <span class="n">df_demo</span><span class="p">[</span><span class="s2">"C"</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span>
@@ -19226,7 +19226,7 @@ Name: C, dtype: bool</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[54]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[59]:</div>
@@ -19305,7 +19305,7 @@ Name: C, dtype: bool</pre>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [55]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [60]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">tail</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
@@ -19326,7 +19326,7 @@ Name: C, dtype: bool</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[55]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[60]:</div>
@@ -19400,18 +19400,18 @@ Name: C, dtype: bool</pre>
</div>
-</div><div class="fragment"><div class="jp-Cell jp-CodeCell jp-Notebook-cell ">
+</div></section><section><div class="jp-Cell jp-CodeCell jp-Notebook-cell ">
<div class="jp-Cell-inputWrapper">
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [63]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [69]:</div>
<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_demo</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
<span class="p">{</span><span class="s2">"A"</span><span class="p">:</span> <span class="mf">1.3</span><span class="p">,</span> <span class="s2">"B"</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timestamp</span><span class="p">(</span><span class="s2">"2018-02-27"</span><span class="p">),</span> <span class="s2">"C"</span><span class="p">:</span> <span class="o">-</span><span class="mf">0.777</span><span class="p">,</span> <span class="s2">"D"</span><span class="p">:</span> <span class="s2">"has it?"</span><span class="p">,</span> <span class="s2">"E"</span><span class="p">:</span> <span class="s2">"Same"</span><span class="p">,</span> <span class="s2">"F"</span><span class="p">:</span> <span class="mi">23</span><span class="p">},</span>
<span class="n">ignore_index</span><span class="o">=</span><span class="kc">True</span>
-<span class="p">)</span> <span class="c1"># TODO: Fix me</span>
+<span class="p">)</span>
</pre></div>
</div>
@@ -19433,7 +19433,7 @@ Name: C, dtype: bool</pre>
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
-<pre>/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/2974913581.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
+<pre>/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/363555535.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
df_demo.append(
</pre>
</div>
@@ -19442,7 +19442,7 @@ Name: C, dtype: bool</pre>
<div class="jp-OutputArea-child">
- <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[63]:</div>
+ <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[69]:</div>
@@ -19546,6 +19546,25 @@ Name: C, dtype: bool</pre>
</div>
+</div><div class="fragment">
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown">
+<p><code>.append()</code> seems to be deprecated; one needs to use something like the following in thef future:</p>
+<div class="highlight"><pre><span></span><span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span>
+ <span class="p">[</span>
+ <span class="n">df_demo</span><span class="p">,</span>
+ <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s2">"A"</span><span class="p">:</span> <span class="mf">1.3</span><span class="p">,</span> <span class="s2">"B"</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timestamp</span><span class="p">(</span><span class="s2">"2018-02-27"</span><span class="p">),</span> <span class="s2">"C"</span><span class="p">:</span> <span class="o">-</span><span class="mf">0.777</span><span class="p">,</span> <span class="s2">"D"</span><span class="p">:</span> <span class="s2">"has it?"</span><span class="p">,</span> <span class="s2">"E"</span><span class="p">:</span> <span class="s2">"Same"</span><span class="p">,</span> <span class="s2">"F"</span><span class="p">:</span> <span class="mi">23</span><span class="p">},</span> <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
+ <span class="p">],</span> <span class="n">ignore_index</span><span class="o">=</span><span class="kc">True</span>
+<span class="p">)</span>
+</pre></div>
+
+</div>
+</div>
+</div>
</div></div></section><section>
<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
<div class="jp-Cell-inputWrapper">
diff --git a/Introduction-to-Pandas--slides.ipynb b/Introduction-to-Pandas--slides.ipynb
index 0d318a3a4123ec619424d1133dcdd804010e7564..ac333c1c51eff0fa61d51eb9af6f0dff054993c3 100644
--- a/Introduction-to-Pandas--slides.ipynb
+++ b/Introduction-to-Pandas--slides.ipynb
@@ -150,7 +150,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 7,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -163,7 +163,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 8,
"metadata": {
"exercise": "task",
"slideshow": {
@@ -177,7 +177,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 9,
"metadata": {
"slideshow": {
"slide_type": "-"
@@ -190,7 +190,7 @@
"'1.4.2'"
]
},
- "execution_count": 3,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -201,7 +201,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 10,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -314,7 +314,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 11,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -327,7 +327,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 12,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -417,7 +417,7 @@
"9 60"
]
},
- "execution_count": 6,
+ "execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
@@ -428,7 +428,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 13,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -483,7 +483,7 @@
"2 56"
]
},
- "execution_count": 7,
+ "execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@@ -506,7 +506,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 14,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -531,7 +531,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 15,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -596,7 +596,7 @@
"3 Waters 57"
]
},
- "execution_count": 8,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
@@ -620,7 +620,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
@@ -629,7 +629,7 @@
"Index(['Name', 'Age'], dtype='object')"
]
},
- "execution_count": 9,
+ "execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
@@ -652,7 +652,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
@@ -661,7 +661,7 @@
"RangeIndex(start=0, stop=10, step=1)"
]
},
- "execution_count": 10,
+ "execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
@@ -684,7 +684,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 18,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -779,7 +779,7 @@
"Hall 60"
]
},
- "execution_count": 11,
+ "execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
@@ -802,7 +802,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 19,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -882,7 +882,7 @@
"max 60.000000"
]
},
- "execution_count": 12,
+ "execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
@@ -893,7 +893,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 20,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -956,7 +956,7 @@
"Age 41 56 56 57 39 59 43 56 38 60"
]
},
- "execution_count": 13,
+ "execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
@@ -967,7 +967,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 21,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -982,7 +982,7 @@
" dtype='object', name='Name')"
]
},
- "execution_count": 14,
+ "execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
@@ -1004,7 +1004,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 22,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -1064,7 +1064,7 @@
"Rivers 112"
]
},
- "execution_count": 15,
+ "execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
@@ -1075,7 +1075,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 23,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -1134,7 +1134,7 @@
"2 RiversRivers 112"
]
},
- "execution_count": 16,
+ "execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
@@ -1145,7 +1145,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 24,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -1205,7 +1205,7 @@
"Rivers 28.0"
]
},
- "execution_count": 17,
+ "execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
@@ -1216,7 +1216,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 25,
"metadata": {
"slideshow": {
"slide_type": "subslide"
@@ -1276,7 +1276,7 @@
"Rivers 3136"
]
},
- "execution_count": 18,
+ "execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
@@ -1287,7 +1287,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 26,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -1358,7 +1358,7 @@
"Rice 1521"
]
},
- "execution_count": 19,
+ "execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
@@ -1373,7 +1373,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 27,
"metadata": {
"slideshow": {
"slide_type": "skip"
@@ -1386,7 +1386,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 28,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -1457,7 +1457,7 @@
"Rice 1521"
]
},
- "execution_count": 21,
+ "execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
@@ -1480,7 +1480,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 29,
"metadata": {
"tags": []
},
@@ -1573,7 +1573,7 @@
"Hall True"
]
},
- "execution_count": 22,
+ "execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
@@ -1584,7 +1584,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 30,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -1655,7 +1655,7 @@
"Rice True"
]
},
- "execution_count": 23,
+ "execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
@@ -1687,7 +1687,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 31,
"metadata": {
"exercise": "task",
"slideshow": {
@@ -1706,7 +1706,7 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": 32,
"metadata": {
"exercise": "solution",
"slideshow": {
@@ -1776,7 +1776,7 @@
"Favourite Color violet gray "
]
},
- "execution_count": 25,
+ "execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
@@ -1804,7 +1804,7 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 33,
"metadata": {},
"outputs": [
{
@@ -1889,7 +1889,7 @@
"4 1.2 2018-02-26 -0.718282 entries Same"
]
},
- "execution_count": 26,
+ "execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
@@ -1907,7 +1907,7 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 34,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -1996,7 +1996,7 @@
"1 1.2 2018-02-26 1.718282 column Same"
]
},
- "execution_count": 27,
+ "execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
@@ -2007,7 +2007,7 @@
},
{
"cell_type": "code",
- "execution_count": 28,
+ "execution_count": 35,
"metadata": {
"slideshow": {
"slide_type": "subslide"
@@ -2069,7 +2069,7 @@
"4 1.2 2018-02-26 -0.72 entries Same"
]
},
- "execution_count": 28,
+ "execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
@@ -2080,7 +2080,7 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": 36,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -2091,7 +2091,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/1325867503.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n",
+ "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/1325867503.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n",
" df_demo.round(2).sum()\n"
]
},
@@ -2104,7 +2104,7 @@
"dtype: object"
]
},
- "execution_count": 31,
+ "execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
@@ -2115,7 +2115,7 @@
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": 37,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -2144,7 +2144,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/3396683912.py:1: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
+ "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/3396683912.py:1: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
" print(df_demo.round(2).to_latex())\n"
]
}
@@ -2182,7 +2182,7 @@
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": 38,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -2265,7 +2265,7 @@
"Walt Malcolm David Kelley False"
]
},
- "execution_count": 33,
+ "execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
@@ -2295,7 +2295,7 @@
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": 39,
"metadata": {
"exercise": "task"
},
@@ -2323,7 +2323,7 @@
},
{
"cell_type": "code",
- "execution_count": 35,
+ "execution_count": 40,
"metadata": {
"exercise": "solution",
"slideshow": {
@@ -2547,7 +2547,7 @@
"[5 rows x 21 columns]"
]
},
- "execution_count": 35,
+ "execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
@@ -2617,7 +2617,7 @@
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": 41,
"metadata": {},
"outputs": [
{
@@ -2684,7 +2684,7 @@
"2 1.2 2018-02-26 -1.304068 has Same"
]
},
- "execution_count": 36,
+ "execution_count": 41,
"metadata": {},
"output_type": "execute_result"
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@@ -2695,7 +2695,7 @@
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": 42,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -2714,7 +2714,7 @@
"Name: C, dtype: float64"
]
},
- "execution_count": 37,
+ "execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
@@ -2737,7 +2737,7 @@
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{
"cell_type": "code",
- "execution_count": 38,
+ "execution_count": 43,
"metadata": {
"tags": []
},
@@ -2753,7 +2753,7 @@
"Name: C, dtype: float64"
]
},
- "execution_count": 38,
+ "execution_count": 43,
"metadata": {},
"output_type": "execute_result"
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@@ -2784,7 +2784,7 @@
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{
"cell_type": "code",
- "execution_count": 39,
+ "execution_count": 44,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -2855,7 +2855,7 @@
"4 1.2 -0.718282"
]
},
- "execution_count": 39,
+ "execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
@@ -2879,7 +2879,7 @@
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{
"cell_type": "code",
- "execution_count": 40,
+ "execution_count": 45,
"metadata": {},
"outputs": [
{
@@ -2937,7 +2937,7 @@
"2 1.2 2018-02-26 -1.304068 has Same"
]
},
- "execution_count": 40,
+ "execution_count": 45,
"metadata": {},
"output_type": "execute_result"
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@@ -2948,7 +2948,7 @@
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{
"cell_type": "code",
- "execution_count": 41,
+ "execution_count": 46,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -3011,7 +3011,7 @@
"3 1.2 2018-02-26 0.986231 entries Same"
]
},
- "execution_count": 41,
+ "execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
@@ -3033,7 +3033,7 @@
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": 47,
"metadata": {},
"outputs": [
{
@@ -3091,7 +3091,7 @@
"2 1.2 2018-02-26 -1.304068 has Same"
]
},
- "execution_count": 42,
+ "execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
@@ -3102,7 +3102,7 @@
},
{
"cell_type": "code",
- "execution_count": 43,
+ "execution_count": 48,
"metadata": {},
"outputs": [
{
@@ -3160,7 +3160,7 @@
"4 1.2 2018-02-26 -0.718282 entries Same"
]
},
- "execution_count": 43,
+ "execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
@@ -3187,7 +3187,7 @@
},
{
"cell_type": "code",
- "execution_count": 44,
+ "execution_count": 49,
"metadata": {
"tags": []
},
@@ -3247,7 +3247,7 @@
"2 1.2 2018-02-26 -1.304068 has Same"
]
},
- "execution_count": 44,
+ "execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
@@ -3270,7 +3270,7 @@
},
{
"cell_type": "code",
- "execution_count": 45,
+ "execution_count": 50,
"metadata": {},
"outputs": [
{
@@ -3319,7 +3319,7 @@
"2 1.2 -1.304068"
]
},
- "execution_count": 45,
+ "execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
@@ -3343,7 +3343,7 @@
},
{
"cell_type": "code",
- "execution_count": 46,
+ "execution_count": 51,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -3434,7 +3434,7 @@
"entries 1.2 2018-02-26 -0.718282 Same"
]
},
- "execution_count": 46,
+ "execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
@@ -3446,7 +3446,7 @@
},
{
"cell_type": "code",
- "execution_count": 47,
+ "execution_count": 52,
"metadata": {},
"outputs": [
{
@@ -3509,7 +3509,7 @@
"entries 1.2 2018-02-26 -0.718282 Same"
]
},
- "execution_count": 47,
+ "execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
@@ -3520,7 +3520,7 @@
},
{
"cell_type": "code",
- "execution_count": 48,
+ "execution_count": 53,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -3586,7 +3586,7 @@
"entries 1.2 -0.718282"
]
},
- "execution_count": 48,
+ "execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
@@ -3616,7 +3616,7 @@
},
{
"cell_type": "code",
- "execution_count": 49,
+ "execution_count": 54,
"metadata": {},
"outputs": [
{
@@ -3674,7 +3674,7 @@
"3 1.2 2018-02-26 0.986231 entries Same"
]
},
- "execution_count": 49,
+ "execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
@@ -3685,7 +3685,7 @@
},
{
"cell_type": "code",
- "execution_count": 50,
+ "execution_count": 55,
"metadata": {},
"outputs": [
{
@@ -3699,7 +3699,7 @@
"Name: C, dtype: bool"
]
},
- "execution_count": 50,
+ "execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
@@ -3710,7 +3710,7 @@
},
{
"cell_type": "code",
- "execution_count": 51,
+ "execution_count": 56,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -3763,7 +3763,7 @@
"4 1.2 2018-02-26 -0.718282 entries Same"
]
},
- "execution_count": 51,
+ "execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
@@ -3793,7 +3793,7 @@
},
{
"cell_type": "code",
- "execution_count": 52,
+ "execution_count": 57,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -3864,7 +3864,7 @@
"2 1.2 2018-02-26 -1.304068 has Same"
]
},
- "execution_count": 52,
+ "execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
@@ -3875,7 +3875,7 @@
},
{
"cell_type": "code",
- "execution_count": 53,
+ "execution_count": 58,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -3951,7 +3951,7 @@
"2 1.2 2018-02-26 -1.304068 has Same -2.504068"
]
},
- "execution_count": 53,
+ "execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
@@ -3976,7 +3976,7 @@
},
{
"cell_type": "code",
- "execution_count": 54,
+ "execution_count": 59,
"metadata": {
"slideshow": {
"slide_type": "fragment"
@@ -4056,7 +4056,7 @@
"2 1.2 2018-02-26 -1.304068 has Same 1.700594 -2.504068"
]
},
- "execution_count": 54,
+ "execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
@@ -4068,11 +4068,16 @@
},
{
"cell_type": "code",
- "execution_count": 55,
+ "execution_count": 60,
"metadata": {
+ "collapsed": true,
+ "jupyter": {
+ "outputs_hidden": true
+ },
"slideshow": {
"slide_type": "subslide"
- }
+ },
+ "tags": []
},
"outputs": [
{
@@ -4147,7 +4152,7 @@
"4 1.2 2018-02-26 -0.718282 entries Same 0.515929 -1.918282"
]
},
- "execution_count": 55,
+ "execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
@@ -4158,18 +4163,19 @@
},
{
"cell_type": "code",
- "execution_count": 63,
+ "execution_count": 69,
"metadata": {
"slideshow": {
- "slide_type": "fragment"
- }
+ "slide_type": "subslide"
+ },
+ "tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
- "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_62318/2974913581.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
+ "/var/folders/f5/swf8tg5j5r7bqbwftt3zn6b00000gn/T/ipykernel_67517/363555535.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
" df_demo.append(\n"
]
},
@@ -4278,7 +4284,7 @@
"5 1.3 2018-02-27 -0.777000 has it? Same NaN 23.000000"
]
},
- "execution_count": 63,
+ "execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
@@ -4287,7 +4293,27 @@
"df_demo.append(\n",
" {\"A\": 1.3, \"B\": pd.Timestamp(\"2018-02-27\"), \"C\": -0.777, \"D\": \"has it?\", \"E\": \"Same\", \"F\": 23},\n",
" ignore_index=True\n",
- ") # TODO: Fix me"
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "slideshow": {
+ "slide_type": "fragment"
+ },
+ "tags": []
+ },
+ "source": [
+ "`.append()` seems to be deprecated; one needs to use something like the following in thef future:\n",
+ "```python\n",
+ "pd.concat(\n",
+ " [\n",
+ " df_demo, \n",
+ " pd.DataFrame({\"A\": 1.3, \"B\": pd.Timestamp(\"2018-02-27\"), \"C\": -0.777, \"D\": \"has it?\", \"E\": \"Same\", \"F\": 23}, index=[0])\n",
+ " ], ignore_index=True\n",
+ ")\n",
+ "```"
]
},
{
@@ -7282,10 +7308,10 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.2"
+ "version": "3.10.4"
},
"toc-autonumbering": false,
- "toc-showcode": true,
+ "toc-showcode": false,
"toc-showmarkdowntxt": false,
"toc-showtags": true
},
diff --git a/Introduction-to-Pandas--solution.ipynb b/Introduction-to-Pandas--solution.ipynb
index dd553efdb4cc9bcd2a1282c0d283ee41439d5f3c..70ad75c1cb769afa9cc558ebe1d901b4e8a2d8a5 100644
--- a/Introduction-to-Pandas--solution.ipynb
+++ b/Introduction-to-Pandas--solution.ipynb
@@ -51,7 +51,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 8,
"metadata": {
"exercise": "task",
"slideshow": {
@@ -102,7 +102,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 31,
"metadata": {
"exercise": "task",
"slideshow": {
@@ -121,7 +121,7 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": 32,
"metadata": {
"exercise": "solution",
"slideshow": {
@@ -191,7 +191,7 @@
"Favourite Color violet gray "
]
},
- "execution_count": 25,
+ "execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
@@ -227,7 +227,7 @@
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": 39,
"metadata": {
"exercise": "task"
},
@@ -255,7 +255,7 @@
},
{
"cell_type": "code",
- "execution_count": 35,
+ "execution_count": 40,
"metadata": {
"exercise": "solution",
"slideshow": {
@@ -479,7 +479,7 @@
"[5 rows x 21 columns]"
]
},
- "execution_count": 35,
+ "execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
@@ -1253,10 +1253,10 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.2"
+ "version": "3.10.4"
},
"toc-autonumbering": false,
- "toc-showcode": true,
+ "toc-showcode": false,
"toc-showmarkdowntxt": false,
"toc-showtags": true
},
diff --git a/Introduction-to-Pandas--tasks.ipynb b/Introduction-to-Pandas--tasks.ipynb
index 7a901d76b9b3e0a077b41edd6da28e8237581929..cdfe751753a6858dd889361ca2ecdbf1f222752c 100644
--- a/Introduction-to-Pandas--tasks.ipynb
+++ b/Introduction-to-Pandas--tasks.ipynb
@@ -51,7 +51,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 8,
"metadata": {
"exercise": "task",
"slideshow": {
@@ -102,7 +102,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 31,
"metadata": {
"exercise": "task",
"slideshow": {
@@ -140,7 +140,7 @@
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": 39,
"metadata": {
"exercise": "task"
},
@@ -333,10 +333,10 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.2"
+ "version": "3.10.4"
},
"toc-autonumbering": false,
- "toc-showcode": true,
+ "toc-showcode": false,
"toc-showmarkdowntxt": false,
"toc-showtags": true
},
diff --git a/custom.css b/custom.css
index 3311bd7cf6972d42d66ecceba5380328089f2646..f5dbb4d43bca70a46fed2185f887ac7c572d3a86 100644
--- a/custom.css
+++ b/custom.css
@@ -11,3 +11,12 @@ span.task {
right: 10px;
top: 10px;
}
+
+.jp-RenderedText[data-mime-type="application/vnd.jupyter.stderr"] {
+ font-size: 1.2rem;
+}
+
+.reveal .jp-RenderedHTMLCommon pre {
+ box-shadow: initial;
+ /*border-left: 3px solid rgba(0, 0, 0, 0.15);*/
+}
\ No newline at end of file
diff --git a/fzj-reveal.js b/fzj-reveal.js
index 6eabaeb69aa35c1872c7039639de9e1b9f55e8ec..157ad1f57942c70b22386ed8b8add17575574656 160000
--- a/fzj-reveal.js
+++ b/fzj-reveal.js
@@ -1 +1 @@
-Subproject commit 6eabaeb69aa35c1872c7039639de9e1b9f55e8ec
+Subproject commit 157ad1f57942c70b22386ed8b8add17575574656