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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Plotting\n, hello" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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UCH/meFcSEX582Xhq6hq4b9UOkhNiuWvOKK9jmQhWcqia1Tv2c/c5o4mxhoYm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\nRU5ErkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x1062832e8>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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Hqj5W1QtEZD/g3cRJAFXVyLtUIIzEx0STm5FCbkYK942DjwoL6XHaqOMn3Oet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\n1r8a+IUz3u3t1VQuV7fXSRnHAe+Ew/b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| |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x1046b9780>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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Uu/uXpTb8eHeE14uINCg/HtGLtGYJ/HLi4rKbq0k5kXo9nWtm5wJzzOxlM/uG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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10fc43b70>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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zvv7D9fvZc+wM94/tbY2JjAlBbp31NE9Vu6lqrKomq+qVzuPvqOoA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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10fd8a400>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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umzgy7DgikmSi9SH82syOaeK97mZ2jZld2doNe0RF8DQ9mJL6TmynF/Tn1BH9uH/+Gipr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\n+mqqajR4XmdWW+f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| |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10fee65c0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"\n", | |
"\n", | |
"#x\n", | |
"Conc = [10, 20, 30, 40, 50]\n", | |
"\n", | |
"#f(x)\n", | |
"FerricChlorideAC = [0.33, -0.59, -0.76, 1.53, 1.23]\n", | |
"AlumAC = [-0.967, -3, -6.17, -5.53, -14.8]\n", | |
"Alum = [4.9, -17.2, 3.5, 8.1, -4.2]\n", | |
"Alum2 = [6.36, 0.43, -1.13, -0.36, -0.63]\n", | |
"FerricChloride = [-4.67, -4.8, -5.4, -4, -5.13]\n", | |
"\n", | |
"\n", | |
"#Construct dataframe\n", | |
"Data = {'Ferric Chloride AC' : FerricChlorideAC, \n", | |
" 'Ferric Chloride' : FerricChloride,\n", | |
" 'Alum AC' : AlumAC,\n", | |
" 'Alum' : Alum,\n", | |
" 'Alum 2' : Alum2\n", | |
" }\n", | |
"\n", | |
"for item in Data:\n", | |
" plt.plot(Conc, Data[item])\n", | |
" plt.xlabel('Concentration (mg/L)')\n", | |
" plt.ylabel('Turbidity (NTU)')\n", | |
" plt.title(item)\n", | |
" plt.grid(True)\n", | |
" plt.savefig(\"/Users/BrianBadahdah/Documents/Photos\" +\n", | |
" \"/Screenshots/\"+item+\".jpg\", format='jpeg')\n", | |
" plt.show()\n", | |
" " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 27, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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ZuGAzX6/YzTVJsdw3LIFWDep4HdGUQ2hoKHFxca5sOzU1lV69ermy7cqojlyunT4Ska44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\nuDMCXd3qf8jPioIxxlS34FBo28+Zhv0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| |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10fc0f6a0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"\n", | |
"Alum1pH = [8.54, 9.64, 9.34, 8.17, 8.27]\n", | |
"\n", | |
"Alum2pH = [8.816666667, 8.53, 8.326666667, 8.296666667, 8.133333333]\n", | |
"\n", | |
"\n", | |
"Alum1, = plt.plot(Conc, Alum1pH, label = 'Alum 1')\n", | |
"Alum2, = plt.plot(Conc, Alum2pH, label = 'Alum 2')\n", | |
"\n", | |
"\n", | |
"legend = plt.legend(handles=[Alum1, Alum2], loc=1)\n", | |
"\n", | |
"plt.xlabel('Concentration (mg/L)')\n", | |
"plt.ylabel('pH')\n", | |
"plt.title(\"pH Plot\")\n", | |
"plt.grid(True)\n", | |
"plt.savefig(\"/Users/BrianBadahdah/Documents/Photos\" +\n", | |
" \"/Screenshots/\"+\"pH\"+\".jpg\", format='jpeg')\n", | |
"plt.show()\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 15, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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mlbXdgipQcjTGLyLVgOuBVVlClYDDmb6Oc2673Hal8q+ana2ZP61GAFkKetIJ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\nSikVYLTwK6VUgPl/Ln/0Y49SLIkAAAAASUVORK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x1107426a0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"\n", | |
"line1, = plt.plot([1,2,3], label=\"Line 1\", linestyle='--')\n", | |
"line2, = plt.plot([3,2,1], label=\"Line 2\", linewidth=4)\n", | |
"\n", | |
"# Create a legend for the first line.\n", | |
"first_legend = plt.legend(handles=[line1], loc=1)\n", | |
"\n", | |
"# Add the legend manually to the current Axes.\n", | |
"ax = plt.gca().add_artist(first_legend)\n", | |
"\n", | |
"# Create another legend for the second line.\n", | |
"plt.legend(handles=[line2], loc=4)\n", | |
"\n", | |
"plt.show()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.6.0" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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