diff --git a/day2/1-other-kernel/Julia.ipynb b/day2/1-other-kernel/Julia.ipynb
index 7914744f57b32ab220dfa07e1833676bad4b6145..d71743bb42eb49f49e3ef0c39e5d2d9f91cfdb53 100644
--- a/day2/1-other-kernel/Julia.ipynb
+++ b/day2/1-other-kernel/Julia.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "markdown",
- "id": "planned-damage",
+ "id": "suburban-division",
"metadata": {},
"source": [
"Example from https://datascience-enthusiast.com/Miscellaneous/Jupyter_R_Python_Julia_Octave.html"
@@ -10,43 +10,261 @@
},
{
"cell_type": "code",
- "execution_count": null,
- "id": "immediate-protocol",
+ "execution_count": 1,
+ "id": "micro-lawsuit",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
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+ " 448.767,511.71 447.401,515.804 446.094,519.913 444.845,524.035 443.656,528.17 442.526,532.318 441.456,536.478 440.447,540.65 439.497,544.832 438.609,549.025 \n",
+ " 437.781,553.228 437.015,557.44 436.31,561.661 435.667,565.891 435.085,570.128 434.566,574.372 434.109,578.623 433.715,582.88 433.383,587.143 433.114,591.411 \n",
+ " 432.908,595.683 432.766,599.959 432.686,604.239 432.67,608.521 432.717,612.805 432.828,617.091 433.003,621.379 433.241,625.666 433.543,629.954 433.909,634.241 \n",
+ " 434.339,638.527 434.833,642.811 435.39,647.093 436.011,651.373 436.696,655.648 437.445,659.92 438.258,664.188 439.134,668.45 440.074,672.707 441.078,676.957 \n",
+ " 442.145,681.201 443.275,685.438 444.468,689.666 445.724,693.887 447.044,698.099 448.426,702.301 449.87,706.493 451.377,710.675 452.946,714.846 454.576,719.006 \n",
+ " 456.269,723.154 458.022,727.289 459.837,731.411 461.713,735.52 463.649,739.615 465.645,743.695 467.702,747.76 469.818,751.811 471.993,755.845 474.227,759.863 \n",
+ " 476.519,763.865 478.87,767.849 481.278,771.816 483.743,775.764 486.266,779.695 488.844,783.607 491.479,787.499 494.169,791.372 496.914,795.225 499.713,799.058 \n",
+ " 502.567,802.871 505.473,806.662 508.433,810.432 511.445,814.181 514.509,817.908 517.624,821.613 520.789,825.295 524.005,828.955 527.27,832.592 530.584,836.206 \n",
+ " 533.945,839.796 537.355,843.364 540.811,846.907 544.313,850.427 547.861,853.923 551.454,857.394 555.091,860.842 558.771,864.265 562.493,867.664 566.258,871.039 \n",
+ " 570.064,874.389 573.911,877.715 577.797,881.016 581.722,884.293 585.686,887.546 589.686,890.774 593.724,893.978 597.797,897.158 601.906,900.315 606.049,903.447 \n",
+ " 610.225,906.556 614.434,909.641 618.675,912.704 622.947,915.743 627.249,918.76 631.581,921.754 635.941,924.726 640.33,927.677 644.745,930.607 649.187,933.515 \n",
+ " 653.654,936.403 658.146,939.271 662.661,942.12 667.2,944.95 671.761,947.761 676.343,950.554 680.946,953.33 685.569,956.089 690.212,958.832 694.872,961.56 \n",
+ " 699.55,964.273 704.246,966.973 708.957,969.659 713.684,972.332 718.425,974.995 723.181,977.646 727.95,980.287 732.732,982.92 737.526,985.545 742.332,988.162 \n",
+ " 747.148,990.774 751.975,993.38 756.812,995.982 761.658,998.582 766.513,1001.18 771.376,1003.78 776.246,1006.37 781.124,1008.97 786.009,1011.58 790.901,1014.18 \n",
+ " 795.799,1016.79 800.702,1019.41 805.612,1022.04 810.526,1024.67 815.446,1027.32 820.371,1029.98 825.3,1032.65 830.234,1035.33 835.173,1038.04 840.116,1040.76 \n",
+ " 845.064,1043.5 850.016,1046.26 854.973,1049.04 859.935,1051.85 864.901,1054.68 869.873,1057.54 874.85,1060.43 879.833,1063.35 884.822,1066.3 889.817,1069.28 \n",
+ " 894.819,1072.3 899.828,1075.36 904.846,1078.46 909.871,1081.59 914.906,1084.77 919.951,1087.99 925.005,1091.26 930.072,1094.58 935.15,1097.95 940.241,1101.37 \n",
+ " 945.346,1104.84 950.466,1108.36 955.602,1111.95 960.756,1115.59 965.927,1119.29 971.117,1123.06 976.328,1126.89 981.561,1130.79 986.818,1134.76 992.099,1138.8 \n",
+ " 997.406,1142.92 1002.74,1147.11 1008.1,1151.38 1013.5,1155.73 1018.93,1160.16 1024.39,1164.68 1029.89,1169.29 1035.42,1173.99 1041,1178.79 1046.61,1183.69 \n",
+ " 1052.27,1188.69 1057.98,1193.79 1063.73,1199 1069.54,1204.33 1075.39,1209.78 1081.3,1215.35 1087.27,1221.06 1093.3,1226.9 1099.39,1232.88 1105.54,1239.02 \n",
+ " 1111.76,1245.32 1118.06,1251.79 1124.42,1258.44 1130.87,1265.29 1137.39,1272.35 1143.99,1279.65 1150.69,1287.2 1157.47,1295.04 1164.35,1303.18 1171.34,1311.69 \n",
+ " 1178.43,1320.6 1185.63,1329.98 1192.95,1339.93 1200.4,1350.56 1207.99,1362.04 1215.72,1374.63 1223.63,1388.77 1231.73,1405.25 1240.06,1425.98 1248.72,1459.42 \n",
+ " 1257.61,1439.63 1266.08,1414.87 1274.29,1396.64 1282.29,1381.47 1290.11,1368.17 1297.77,1356.18 1305.29,1345.15 1312.67,1334.88 1319.94,1325.23 1327.08,1316.09 \n",
+ " 1334.11,1307.39 1341.05,1299.07 1347.88,1291.08 1354.62,1283.39 1361.27,1275.97 1367.83,1268.79 1374.31,1261.84 1380.72,1255.09 1387.04,1248.53 1393.3,1242.15 \n",
+ " 1399.49,1235.93 1405.61,1229.87 1411.67,1223.96 1417.67,1218.19 1423.61,1212.55 1429.49,1207.04 1435.32,1201.65 1441.1,1196.38 1446.83,1191.22 1452.51,1186.17 \n",
+ " 1458.15,1181.23 1463.74,1176.38 1469.3,1171.63 1474.81,1166.98 1480.29,1162.41 1485.74,1157.93 1491.15,1153.54 1496.53,1149.23 1501.88,1145 1507.2,1140.85 \n",
+ " 1512.49,1136.77 1517.76,1132.77 1523,1128.83 1528.23,1124.97 1533.43,1121.17 1538.61,1117.43 1543.77,1113.76 1548.91,1110.15 1554.04,1106.59 1559.15,1103.09 \n",
+ " 1564.25,1099.65 1569.34,1096.26 1574.41,1092.92 1579.47,1089.62 1584.52,1086.38 1589.56,1083.18 1594.59,1080.02 1599.61,1076.9 1604.62,1073.83 1609.63,1070.79 \n",
+ " 1614.63,1067.79 1619.62,1064.82 1624.61,1061.88 1629.59,1058.98 1634.56,1056.11 1639.53,1053.26 1644.49,1050.44 1649.45,1047.65 1654.41,1044.87 1659.36,1042.12 \n",
+ " 1664.3,1039.39 1669.24,1036.68 1674.18,1033.99 1679.11,1031.31 1684.04,1028.65 1688.96,1025.99 1693.88,1023.35 1698.79,1020.72 1703.7,1018.1 1708.6,1015.49 \n",
+ " 1713.49,1012.88 1718.38,1010.27 1723.26,1007.67 1728.14,1005.08 1733,1002.48 1737.86,999.881 1742.71,997.282 1747.55,994.682 1752.39,992.077 1757.21,989.469 \n",
+ " 1762.02,986.854 1766.82,984.233 1771.61,981.605 1776.38,978.968 1781.15,976.321 1785.89,973.665 1790.63,970.997 1795.35,968.317 1800.05,965.625 1804.74,962.919 \n",
+ " 1809.41,960.198 1814.06,957.463 1818.69,954.712 1823.3,951.944 1827.9,949.16 1832.47,946.358 1837.02,943.537 1841.55,940.698 1846.05,937.84 1850.53,934.962 \n",
+ " 1854.98,932.063 1859.41,929.145 1863.81,926.204 1868.19,923.243 1872.54,920.26 1876.85,917.254 1881.14,914.226 1885.4,911.175 1889.62,908.101 1893.81,905.004 \n",
+ " 1897.97,901.884 1902.1,898.739 1906.19,895.571 1910.25,892.379 1914.27,889.163 1918.25,885.922 1922.19,882.658 1926.1,879.368 1929.96,876.055 1933.79,872.717 \n",
+ " 1937.58,869.355 1941.32,865.968 1945.02,862.557 1948.68,859.121 1952.29,855.661 1955.87,852.178 1959.39,848.67 1962.87,845.138 1966.3,841.583 1969.69,838.004 \n",
+ " 1973.03,834.402 1976.32,830.776 1979.56,827.128 1982.75,823.457 1985.89,819.763 1988.98,816.047 1992.01,812.309 1995,808.55 1997.93,804.769 2000.81,800.967 \n",
+ " 2003.64,797.144 2006.41,793.301 2009.13,789.438 2011.79,785.555 2014.4,781.653 2016.95,777.732 2019.44,773.792 2021.88,769.835 2024.26,765.859 2026.58,761.866 \n",
+ " 2028.84,757.856 2031.05,753.83 2033.19,749.787 2035.28,745.73 2037.31,741.657 2039.27,737.569 2041.18,733.467 2043.02,729.351 2044.81,725.223 2046.53,721.081 \n",
+ " 2048.19,716.928 2049.79,712.762 2051.33,708.586 2052.81,704.398 2054.22,700.201 2055.57,695.994 2056.86,691.778 2058.08,687.553 2059.24,683.32 2060.34,679.08 \n",
+ " 2061.38,674.833 2062.35,670.579 2063.26,666.319 2064.1,662.054 2064.88,657.785 2065.6,653.511 2066.25,649.233 2066.84,644.953 2067.37,640.669 2067.83,636.384 \n",
+ " 2068.23,632.098 2068.56,627.81 2068.83,623.522 2069.04,619.235 2069.18,614.948 2069.26,610.663 2069.28,606.379 2069.23,602.099 2069.12,597.821 2068.94,593.547 \n",
+ " 2068.71,589.276 2068.41,585.011 2068.04,580.751 2067.62,576.497 2067.13,572.249 2066.58,568.008 2065.97,563.775 2065.29,559.55 2064.56,555.333 2063.76,551.125 \n",
+ " 2062.9,546.927 2061.98,542.74 2061,538.563 2059.96,534.397 2058.86,530.243 2057.7,526.101 2056.48,521.972 2055.21,517.857 2053.87,513.755 2052.47,509.668 \n",
+ " 2051.02,505.595 2049.51,501.538 2047.94,497.497 2046.32,493.472 2044.64,489.464 2042.9,485.474 2041.1,481.501 2039.25,477.546 2037.35,473.61 2035.39,469.694 \n",
+ " 2033.38,465.797 2031.31,461.92 2029.19,458.064 2027.02,454.229 2024.8,450.415 2022.52,446.623 2020.19,442.854 2017.81,439.107 2015.39,435.383 2012.91,431.684 \n",
+ " 2010.38,428.008 2007.8,424.356 2005.18,420.729 2002.5,417.127 1999.78,413.551 1997.02,410.001 1994.2,406.477 1991.35,402.98 1988.44,399.51 1985.5,396.067 \n",
+ " \n",
+ " \"/>\n",
+ "</svg>\n"
+ ]
+ },
+ "execution_count": 1,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"using Plots\n",
- "r(θ)=sin(θ).*√(abs(cos(θ)))./(sin(θ)+7/5)-2sin(θ)+2\n",
+ "r(θ)=sin.(θ).*sqrt.(abs.(cos.(θ)))./(sin.(θ).+7/5)-2sin.(θ).+2\n",
"\n",
"for i in -6:6\n",
" θ=π+i*π/6; \n",
" y=r(θ); \n",
"end\n",
"\n",
- "θ=linspace(0,2*π,1000) \n",
- "x=r(θ).*cos(θ) \n",
- "y=r(θ).*sin(θ)\n",
+ "θ=range(0,stop=2*π,length=1000)\n",
+ "\n",
+ "x=r(θ).*cos.(θ) \n",
+ "y=r(θ).*sin.(θ)\n",
"\n",
"pyplot()\n",
- "plot(x,y, linecolor=:red, leg=false)\n",
- "ax = PyPlot.gca() \n",
- "ax[:set_xlim]((-3,3));\n",
- "ax[:set_ylim]((-4,1));\n",
"plot(x,y, linecolor=:red, leg=false, xlims = (-3,3), ylims=(-4,1), title = \"Heart with Julia\")"
]
}
],
"metadata": {
"kernelspec": {
- "display_name": "Julia 1.5.2",
+ "display_name": "Julia 1.6.1",
"language": "julia",
- "name": "julia-1.5"
+ "name": "julia-1.6"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
- "version": "1.5.2"
+ "version": "1.6.1"
}
},
"nbformat": 4,
diff --git a/day2/1-other-kernel/Octave.ipynb b/day2/1-other-kernel/Octave.ipynb
index 88642275ede9c7bea1689989d8ab4b6eb579711a..ba20702ccbeeffd687268ef7a28a3a5cf4230a17 100644
--- a/day2/1-other-kernel/Octave.ipynb
+++ b/day2/1-other-kernel/Octave.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "markdown",
- "id": "grand-slovak",
+ "id": "monetary-analysis",
"metadata": {},
"source": [
"Example from https://datascience-enthusiast.com/Miscellaneous/Jupyter_R_Python_Julia_Octave.html"
@@ -10,10 +10,21 @@
},
{
"cell_type": "code",
- "execution_count": null,
- "id": "confused-immune",
+ "execution_count": 1,
+ "id": "comic-denver",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<IPython.core.display.Image object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"t=-10:0.01:10;\n",
"x=16*(power(sin(t),3));\n",
@@ -30,7 +41,24 @@
"name": "octave"
},
"language_info": {
- "name": ""
+ "file_extension": ".m",
+ "help_links": [
+ {
+ "text": "GNU Octave",
+ "url": "https://www.gnu.org/software/octave/support.html"
+ },
+ {
+ "text": "Octave Kernel",
+ "url": "https://github.com/Calysto/octave_kernel"
+ },
+ {
+ "text": "MetaKernel Magics",
+ "url": "https://metakernel.readthedocs.io/en/latest/source/README.html"
+ }
+ ],
+ "mimetype": "text/x-octave",
+ "name": "octave",
+ "version": "6.1.0"
}
},
"nbformat": 4,
diff --git a/day2/1-other-kernel/Python3.ipynb b/day2/1-other-kernel/Python3.ipynb
index 71aff26bc774df1e0260056e5286b1a108a9c2b7..535dc0a94560f80caaf4d3219168dbab018bd43e 100644
--- a/day2/1-other-kernel/Python3.ipynb
+++ b/day2/1-other-kernel/Python3.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "markdown",
- "id": "straight-dynamics",
+ "id": "industrial-adams",
"metadata": {},
"source": [
"Example from https://datascience-enthusiast.com/Miscellaneous/Jupyter_R_Python_Julia_Octave.html"
@@ -11,7 +11,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "id": "running-gates",
+ "id": "marine-embassy",
"metadata": {},
"outputs": [
{
diff --git a/day2/1-other-kernel/R.ipynb b/day2/1-other-kernel/R.ipynb
index 39c1cfde65d2f0777a3731696bd51ce7396daebf..6af199f2cbd091c9f2854c0188935f57ea684d64 100644
--- a/day2/1-other-kernel/R.ipynb
+++ b/day2/1-other-kernel/R.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "markdown",
- "id": "certified-guess",
+ "id": "lesbian-horizontal",
"metadata": {},
"source": [
"Example from https://datascience-enthusiast.com/Miscellaneous/Jupyter_R_Python_Julia_Octave.html"
@@ -10,29 +10,34 @@
},
{
"cell_type": "code",
- "execution_count": null,
- "id": "worth-castle",
+ "execution_count": 2,
+ "id": "multiple-riverside",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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21ONKX022hmmILOhzDr8cfEkJJCYCDx8cTGEhqqd4S4OL1+QgJZWbhcREWRmUlh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QNKxW9fH1yivMmYOmMX06GzYwYwaAnx/r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\nEZ9T4BARERGf+3/yMl1++s9gXgAAAABJRU5ErkJggg==",
+ "text/plain": [
+ "Plot with title “Heart with R”"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 300,
+ "width": 360
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
- "using Plots\n",
- "r(θ)=sin(θ).*√(abs(cos(θ)))./(sin(θ)+7/5)-2sin(θ)+2\n",
+ "options(repr.plot.width = 6)\n",
+ "options(repr.plot.height = 5)\n",
"\n",
- "for i in -6:6\n",
- " θ=π+i*π/6; \n",
- " y=r(θ); \n",
- "end\n",
- "\n",
- "θ=linspace(0,2*π,1000) \n",
- "x=r(θ).*cos(θ) \n",
- "y=r(θ).*sin(θ)\n",
- "\n",
- "pyplot()\n",
- "plot(x,y, linecolor=:red, leg=false)\n",
- "ax = PyPlot.gca() \n",
- "ax[:set_xlim]((-3,3));\n",
- "ax[:set_ylim]((-4,1));\n",
- "plot(x,y, linecolor=:red, leg=false, xlims = (-3,3), ylims=(-4,1), title = \"Heart with Julia\")"
+ "t = seq(0, 2*pi, by = 0.01)\n",
+ "x = 16 * sin(t)^3\n",
+ "y = 13 * cos(t) - 5*cos(2*t) - 2*cos(3*t) - cos(4*t)\n",
+ "plot(x, y, main = \"Heart with R\", xlab = \"\", ylab = \"\", col = \"red\")"
]
}
],
@@ -43,10 +48,12 @@
"name": "ir40"
},
"language_info": {
- "file_extension": ".jl",
- "mimetype": "application/julia",
- "name": "julia",
- "version": "1.5.2"
+ "codemirror_mode": "r",
+ "file_extension": ".r",
+ "mimetype": "text/x-r-source",
+ "name": "R",
+ "pygments_lexer": "r",
+ "version": "4.0.2"
}
},
"nbformat": 4,
diff --git a/day3/2-kernelgateway/1-kernelgateway.ipynb b/day3/2-kernelgateway/1-kernelgateway.ipynb
index 9fdf947f3a2c161667f8d7a1fae278e21d09446d..1782e4c5c6da03c173ca5af950fec059f742bd16 100644
--- a/day3/2-kernelgateway/1-kernelgateway.ipynb
+++ b/day3/2-kernelgateway/1-kernelgateway.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "markdown",
- "id": "civic-cinema",
+ "id": "accompanied-throat",
"metadata": {},
"source": [
"### Jupyter Kernel Gateway\n",
@@ -14,7 +14,7 @@
},
{
"cell_type": "markdown",
- "id": "rubber-stuart",
+ "id": "swiss-characterization",
"metadata": {},
"source": [
"#### Exercise 1:\n",
@@ -24,7 +24,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "aging-parish",
+ "id": "elementary-sally",
"metadata": {},
"outputs": [
{
@@ -254,7 +254,7 @@
},
{
"cell_type": "markdown",
- "id": "saved-relation",
+ "id": "painful-involvement",
"metadata": {},
"source": [
"#### Exercise 2:\n",
@@ -264,7 +264,7 @@
},
{
"cell_type": "markdown",
- "id": "normal-supplier",
+ "id": "stable-programming",
"metadata": {},
"source": [
"#### Exercise 2:\n",
@@ -274,7 +274,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "fabulous-russian",
+ "id": "palestinian-evans",
"metadata": {},
"outputs": [
{
@@ -292,7 +292,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "signal-extension",
+ "id": "continuing-chemistry",
"metadata": {},
"outputs": [
{
@@ -336,7 +336,7 @@
},
{
"cell_type": "markdown",
- "id": "military-february",
+ "id": "funny-stand",
"metadata": {},
"source": [
"------------\n",