{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# 09 Geographical Plotting" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": [ "import chart_studio.plotly as py\n", "import plotly.graph_objects as go\n", "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "init_notebook_mode(connected=True) # connect the javascript to the notebook" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "linkText": "Export to plot.ly", "plotlyServerURL": "https://plot.ly", "showLink": false }, "data": [ { "colorbar": { "title": { "text": "Colorbar Title Goes Here" } }, "colorscale": [ [ 0, "rgb(12,51,131)" ], [ 0.25, "rgb(10,136,186)" ], [ 0.5, "rgb(242,211,56)" ], [ 0.75, "rgb(242,143,56)" ], [ 1, "rgb(217,30,30)" ] ], "locationmode": "USA-states", "locations": [ "AZ", "CA", "NY" ], "text": [ "text1", "text2", "text3" ], "type": "choropleth", "z": [ 1, 2, 3 ] } ], "layout": { "geo": { "scope": "usa" }, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "fillpattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "sequentialminus": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } } } }, "text/html": [ "

" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "# dict containing cloropleth datatype\n", "data = dict(\n", " type='choropleth',\n", " # states to consider\n", " locations=['AZ', 'CA', 'NY'],\n", " # mapping type\n", " locationmode='USA-states',\n", " colorscale='Portland',\n", " # text title of states hover effect\n", " text=['text1', 'text2', 'text3'],\n", " z=[1.0, 2.0, 3.0],\n", " colorbar={\n", " # title of colorbar\n", " 'title': 'Colorbar Title Goes Here'\n", " }\n", ")\n", "\n", "layout = dict(\n", " geo={'scope': 'usa'}\n", ")\n", "\n", "choromap = go.Figure(data=[data], layout=layout)\n", "iplot(choromap)" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/html": [ "

\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "

	code	state	category	total exports	beef	pork	poultry	dairy	fruits fresh	fruits proc	total fruits	veggies fresh	veggies proc	total veggies	corn	wheat	cotton	text
0	AL	Alabama	state	1390.63	34.4	10.6	481.0	4.06	8.0	17.1	25.11	5.5	8.9	14.33	34.9	70.0	317.61	Alabama<br>Beef 34.4 Dairy 4.06<br>Fruits 25.1...
1	AK	Alaska	state	13.31	0.2	0.1	0.0	0.19	0.0	0.0	0.00	0.6	1.0	1.56	0.0	0.0	0.00	Alaska<br>Beef 0.2 Dairy 0.19<br>Fruits 0.0 Ve...
2	AZ	Arizona	state	1463.17	71.3	17.9	0.0	105.48	19.3	41.0	60.27	147.5	239.4	386.91	7.3	48.7	423.95	Arizona<br>Beef 71.3 Dairy 105.48<br>Fruits 60...
3	AR	Arkansas	state	3586.02	53.2	29.4	562.9	3.53	2.2	4.7	6.88	4.4	7.1	11.45	69.5	114.5	665.44	Arkansas<br>Beef 53.2 Dairy 3.53<br>Fruits 6.8...
4	CA	California	state	16472.88	228.7	11.1	225.4	929.95	2791.8	5944.6	8736.40	803.2	1303.5	2106.79	34.6	249.3	1064.95	California<br>Beef 228.7 Dairy 929.95<br>Frui...

\n", "

" ], "text/plain": [ " code state category total exports beef pork poultry dairy \n", "0 AL Alabama state 1390.63 34.4 10.6 481.0 4.06 \\\n", "1 AK Alaska state 13.31 0.2 0.1 0.0 0.19 \n", "2 AZ Arizona state 1463.17 71.3 17.9 0.0 105.48 \n", "3 AR Arkansas state 3586.02 53.2 29.4 562.9 3.53 \n", "4 CA California state 16472.88 228.7 11.1 225.4 929.95 \n", "\n", " fruits fresh fruits proc total fruits veggies fresh veggies proc \n", "0 8.0 17.1 25.11 5.5 8.9 \\\n", "1 0.0 0.0 0.00 0.6 1.0 \n", "2 19.3 41.0 60.27 147.5 239.4 \n", "3 2.2 4.7 6.88 4.4 7.1 \n", "4 2791.8 5944.6 8736.40 803.2 1303.5 \n", "\n", " total veggies corn wheat cotton \n", "0 14.33 34.9 70.0 317.61 \\\n", "1 1.56 0.0 0.0 0.00 \n", "2 386.91 7.3 48.7 423.95 \n", "3 11.45 69.5 114.5 665.44 \n", "4 2106.79 34.6 249.3 1064.95 \n", "\n", " text \n", "0 Alabama
Beef 34.4 Dairy 4.06
Fruits 25.1... \n", "1 Alaska
Beef 0.2 Dairy 0.19
Fruits 0.0 Ve... \n", "2 Arizona
Beef 71.3 Dairy 105.48
Fruits 60... \n", "3 Arkansas
Beef 53.2 Dairy 3.53
Fruits 6.8... \n", "4 California
Beef 228.7 Dairy 929.95
Frui... " ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.read_csv('2011_US_AGRI_Exports')\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "linkText": "Export to plot.ly", "plotlyServerURL": "https://plot.ly", "showLink": false }, "data": [ { "colorbar": { "title": { "text": "Millions USD" } }, "colorscale": [ [ 0, "rgb(247,252,245)" ], [ 0.125, "rgb(229,245,224)" ], [ 0.25, "rgb(199,233,192)" ], [ 0.375, "rgb(161,217,155)" ], [ 0.5, "rgb(116,196,118)" ], [ 0.625, "rgb(65,171,93)" ], [ 0.75, "rgb(35,139,69)" ], [ 0.875, "rgb(0,109,44)" ], [ 1, "rgb(0,68,27)" ] ], "locationmode": "USA-states", "locations": [ "AL", "AK", "AZ", "AR", "CA", "CO", "CT", "DE", "FL", "GA", "HI", "ID", "IL", "IN", "IA", "KS", "KY", "LA", "ME", "MD", "MA", "MI", "MN", "MS", "MO", "MT", "NE", "NV", "NH", "NJ", "NM", "NY", "NC", "ND", "OH", "OK", "OR", "PA", "RI", "SC", "SD", "TN", "TX", "UT", "VT", "VA", "WA", "WV", "WI", "WY" ], "marker": { "line": { "color": "rgb(255, 255, 255)", "width": 2 } }, "text": [ "Alabama
Beef 34.4 Dairy 4.06
Fruits 25.11 Veggies 14.33
Wheat 70.0 Corn 34.9", "Alaska
Beef 0.2 Dairy 0.19
Fruits 0.0 Veggies 1.56
Wheat 0.0 Corn 0.0", "Arizona
Beef 71.3 Dairy 105.48
Fruits 60.27 Veggies 386.91
Wheat 48.7 Corn 7.3", "Arkansas
Beef 53.2 Dairy 3.53
Fruits 6.88 Veggies 11.45
Wheat 114.5 Corn 69.5", " California
Beef 228.7 Dairy 929.95
Fruits 8736.4 Veggies 2106.79
Wheat 249.3 Corn 34.6", "Colorado
Beef 261.4 Dairy 71.94
Fruits 17.99 Veggies 118.27
Wheat 400.5 Corn 183.2", "Connecticut
Beef 1.1 Dairy 9.49
Fruits 13.1 Veggies 11.16
Wheat 0.0 Corn 0.0", "Delaware
Beef 0.4 Dairy 2.3
Fruits 1.53 Veggies 20.03
Wheat 22.9 Corn 26.9", "Florida
Beef 42.6 Dairy 66.31
Fruits 1371.36 Veggies 450.86
Wheat 1.8 Corn 3.5", "Georgia
Beef 31.0 Dairy 38.38
Fruits 233.51 Veggies 154.77
Wheat 65.4 Corn 57.8", "Hawaii
Beef 4.0 Dairy 1.16
Fruits 55.51 Veggies 24.83
Wheat 0.0 Corn 0.0", "Idaho
Beef 119.8 Dairy 294.6
Fruits 21.64 Veggies 319.19
Wheat 568.2 Corn 24.0", "Illinois
Beef 53.7 Dairy 45.82
Fruits 12.53 Veggies 39.95
Wheat 223.8 Corn 2228.5", "Indiana
Beef 21.9 Dairy 89.7
Fruits 12.98 Veggies 37.89
Wheat 114.0 Corn 1123.2", "Iowa
Beef 289.8 Dairy 107.0
Fruits 3.24 Veggies 7.1
Wheat 3.1 Corn 2529.8", "Kansas
Beef 659.3 Dairy 65.45
Fruits 3.11 Veggies 9.32
Wheat 1426.5 Corn 457.3", "Kentucky
Beef 54.8 Dairy 28.27
Fruits 6.6 Veggies 0.0
Wheat 149.3 Corn 179.1", "Louisiana
Beef 19.8 Dairy 6.02
Fruits 17.83 Veggies 17.25
Wheat 78.7 Corn 91.4", "Maine
Beef 1.4 Dairy 16.18
Fruits 52.01 Veggies 62.9
Wheat 0.0 Corn 0.0", "Maryland
Beef 5.6 Dairy 24.81
Fruits 12.9 Veggies 20.43
Wheat 55.8 Corn 54.1", "Massachusetts
Beef 0.6 Dairy 5.81
Fruits 80.83 Veggies 21.13
Wheat 0.0 Corn 0.0", "Michigan
Beef 37.7 Dairy 214.82
Fruits 257.69 Veggies 189.96
Wheat 247.0 Corn 381.5", "Minnesota
Beef 112.3 Dairy 218.05
Fruits 7.91 Veggies 120.37
Wheat 538.1 Corn 1264.3", "Mississippi
Beef 12.8 Dairy 5.45
Fruits 17.04 Veggies 27.87
Wheat 102.2 Corn 110.0", "Missouri
Beef 137.2 Dairy 34.26
Fruits 13.18 Veggies 17.9
Wheat 161.7 Corn 428.8", "Montana
Beef 105.0 Dairy 6.82
Fruits 3.3 Veggies 45.27
Wheat 1198.1 Corn 5.4", "Nebraska
Beef 762.2 Dairy 30.07
Fruits 2.16 Veggies 53.5
Wheat 292.3 Corn 1735.9", "Nevada
Beef 21.8 Dairy 16.57
Fruits 1.19 Veggies 27.93
Wheat 5.4 Corn 0.0", "New Hampshire
Beef 0.6 Dairy 7.46
Fruits 7.98 Veggies 4.5
Wheat 0.0 Corn 0.0", "New Jersey
Beef 0.8 Dairy 3.37
Fruits 109.45 Veggies 56.54
Wheat 6.7 Corn 10.1", "New Mexico
Beef 117.2 Dairy 191.01
Fruits 101.9 Veggies 43.88
Wheat 13.9 Corn 11.2", "New York
Beef 22.2 Dairy 331.8
Fruits 202.56 Veggies 143.37
Wheat 29.9 Corn 106.1", "North Carolina
Beef 24.8 Dairy 24.9
Fruits 74.47 Veggies 150.45
Wheat 200.3 Corn 92.2", "North Dakota
Beef 78.5 Dairy 8.14
Fruits 0.25 Veggies 130.79
Wheat 1664.5 Corn 236.1", "Ohio
Beef 36.2 Dairy 134.57
Fruits 27.21 Veggies 53.53
Wheat 207.4 Corn 535.1", "Oklahoma
Beef 337.6 Dairy 24.35
Fruits 9.24 Veggies 8.9
Wheat 324.8 Corn 27.5", "Oregon
Beef 58.8 Dairy 63.66
Fruits 315.04 Veggies 126.5
Wheat 320.3 Corn 11.7", "Pennsylvania
Beef 50.9 Dairy 280.87
Fruits 89.48 Veggies 38.26
Wheat 41.0 Corn 112.1", "Rhode Island
Beef 0.1 Dairy 0.52
Fruits 2.83 Veggies 3.02
Wheat 0.0 Corn 0.0", "South Carolina
Beef 15.2 Dairy 7.62
Fruits 53.45 Veggies 42.66
Wheat 55.3 Corn 32.1", "South Dakota
Beef 193.5 Dairy 46.77
Fruits 0.8 Veggies 4.06
Wheat 704.5 Corn 643.6", "Tennessee
Beef 51.1 Dairy 21.18
Fruits 6.23 Veggies 24.67
Wheat 100.0 Corn 88.8", "Texas
Beef 961.0 Dairy 240.55
Fruits 99.9 Veggies 115.23
Wheat 309.7 Corn 167.2", "Utah
Beef 27.9 Dairy 48.6
Fruits 12.34 Veggies 6.6
Wheat 42.8 Corn 5.3", "Vermont
Beef 6.2 Dairy 65.98
Fruits 8.01 Veggies 4.05
Wheat 0.0 Corn 0.0", "Virginia
Beef 39.5 Dairy 47.85
Fruits 36.48 Veggies 27.25
Wheat 77.5 Corn 39.5", "Washington
Beef 59.2 Dairy 154.18
Fruits 1738.57 Veggies 363.79
Wheat 786.3 Corn 29.5", "West Virginia
Beef 12.0 Dairy 3.9
Fruits 11.54 Veggies 0.0
Wheat 1.6 Corn 3.5", "Wisconsin
Beef 107.3 Dairy 633.6
Fruits 133.8 Veggies 148.99
Wheat 96.7 Corn 460.5", "Wyoming
Beef 75.1 Dairy 2.89
Fruits 0.17 Veggies 10.23
Wheat 20.7 Corn 9.0" ], "type": "choropleth", "z": [ 1390.63, 13.31, 1463.17, 3586.02, 16472.88, 1851.33, 259.62, 282.19, 3764.09, 2860.84, 401.84, 2078.89, 8709.48, 5050.23, 11273.76, 4589.01, 1889.15, 1914.23, 278.37, 692.75, 248.65, 3164.16, 7192.33, 2170.8, 3933.42, 1718, 7114.13, 139.89, 73.06, 500.4, 751.58, 1488.9, 3806.05, 3761.96, 3979.79, 1646.41, 1794.57, 1969.87, 31.59, 929.93, 3770.19, 1535.13, 6648.22, 453.39, 180.14, 1146.48, 3894.81, 138.89, 3090.23, 349.69 ] } ], "layout": { "geo": { "lakecolor": "rgb(85, 173, 240)", "scope": "usa", "showlakes": true }, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "fillpattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "sequentialminus": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "2011 US Agriculture Exports by State" } } }, "text/html": [ "

" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data = dict(\n", " type='choropleth',\n", " locations=df['code'],\n", " locationmode='USA-states',\n", " colorscale='Greens',\n", " text=df['text'],\n", " z=df['total exports'],\n", " marker=dict(\n", " line=dict(\n", " color='rgb(255, 255, 255)',\n", " width=2\n", " )\n", " ),\n", " colorbar={'title': 'Millions USD'}\n", ")\n", "\n", "layout = dict(\n", " title='2011 US Agriculture Exports by State',\n", " geo=dict(\n", " scope='usa',\n", " showlakes=True,\n", " lakecolor='rgb(85, 173, 240)'\n", " )\n", ")\n", "\n", "choromap2 = go.Figure(data=[data], layout=layout)\n", "iplot(choromap2)" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "ename": "FileNotFoundError", "evalue": "[Errno 2] No such file or directory: '2014_World_GDP'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[55], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m df \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39;49mread_csv(\u001b[39m'\u001b[39;49m\u001b[39m2014_World_GDP\u001b[39;49m\u001b[39m'\u001b[39;49m)\n\u001b[1;32m 2\u001b[0m df\u001b[39m.\u001b[39mhead()\n", "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/io/parsers/readers.py:912\u001b[0m, in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[0m\n\u001b[1;32m 899\u001b[0m kwds_defaults \u001b[39m=\u001b[39m _refine_defaults_read(\n\u001b[1;32m 900\u001b[0m dialect,\n\u001b[1;32m 901\u001b[0m delimiter,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 908\u001b[0m dtype_backend\u001b[39m=\u001b[39mdtype_backend,\n\u001b[1;32m 909\u001b[0m )\n\u001b[1;32m 910\u001b[0m kwds\u001b[39m.\u001b[39mupdate(kwds_defaults)\n\u001b[0;32m--> 912\u001b[0m \u001b[39mreturn\u001b[39;00m _read(filepath_or_buffer, kwds)\n", "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/io/parsers/readers.py:577\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 574\u001b[0m _validate_names(kwds\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39mnames\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mNone\u001b[39;00m))\n\u001b[1;32m 576\u001b[0m \u001b[39m# Create the parser.\u001b[39;00m\n\u001b[0;32m--> 577\u001b[0m parser \u001b[39m=\u001b[39m TextFileReader(filepath_or_buffer, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwds)\n\u001b[1;32m 579\u001b[0m \u001b[39mif\u001b[39;00m chunksize \u001b[39mor\u001b[39;00m iterator:\n\u001b[1;32m 580\u001b[0m \u001b[39mreturn\u001b[39;00m parser\n", "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/io/parsers/readers.py:1407\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 1404\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39moptions[\u001b[39m\"\u001b[39m\u001b[39mhas_index_names\u001b[39m\u001b[39m\"\u001b[39m] \u001b[39m=\u001b[39m kwds[\u001b[39m\"\u001b[39m\u001b[39mhas_index_names\u001b[39m\u001b[39m\"\u001b[39m]\n\u001b[1;32m 1406\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandles: IOHandles \u001b[39m|\u001b[39m \u001b[39mNone\u001b[39;00m \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m-> 1407\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_engine \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_make_engine(f, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mengine)\n", "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/io/parsers/readers.py:1661\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m 1659\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mb\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m mode:\n\u001b[1;32m 1660\u001b[0m mode \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mb\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m-> 1661\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandles \u001b[39m=\u001b[39m get_handle(\n\u001b[1;32m 1662\u001b[0m f,\n\u001b[1;32m 1663\u001b[0m mode,\n\u001b[1;32m 1664\u001b[0m encoding\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mencoding\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mNone\u001b[39;49;00m),\n\u001b[1;32m 1665\u001b[0m compression\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mcompression\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mNone\u001b[39;49;00m),\n\u001b[1;32m 1666\u001b[0m memory_map\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mmemory_map\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mFalse\u001b[39;49;00m),\n\u001b[1;32m 1667\u001b[0m is_text\u001b[39m=\u001b[39;49mis_text,\n\u001b[1;32m 1668\u001b[0m errors\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mencoding_errors\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39mstrict\u001b[39;49m\u001b[39m\"\u001b[39;49m),\n\u001b[1;32m 1669\u001b[0m storage_options\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mstorage_options\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mNone\u001b[39;49;00m),\n\u001b[1;32m 1670\u001b[0m )\n\u001b[1;32m 1671\u001b[0m \u001b[39massert\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandles \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m\n\u001b[1;32m 1672\u001b[0m f \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandles\u001b[39m.\u001b[39mhandle\n", "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/io/common.py:859\u001b[0m, in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m 854\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(handle, \u001b[39mstr\u001b[39m):\n\u001b[1;32m 855\u001b[0m \u001b[39m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[1;32m 856\u001b[0m \u001b[39m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[1;32m 857\u001b[0m \u001b[39mif\u001b[39;00m ioargs\u001b[39m.\u001b[39mencoding \u001b[39mand\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mb\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m ioargs\u001b[39m.\u001b[39mmode:\n\u001b[1;32m 858\u001b[0m \u001b[39m# Encoding\u001b[39;00m\n\u001b[0;32m--> 859\u001b[0m handle \u001b[39m=\u001b[39m \u001b[39mopen\u001b[39;49m(\n\u001b[1;32m 860\u001b[0m handle,\n\u001b[1;32m 861\u001b[0m ioargs\u001b[39m.\u001b[39;49mmode,\n\u001b[1;32m 862\u001b[0m encoding\u001b[39m=\u001b[39;49mioargs\u001b[39m.\u001b[39;49mencoding,\n\u001b[1;32m 863\u001b[0m errors\u001b[39m=\u001b[39;49merrors,\n\u001b[1;32m 864\u001b[0m newline\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m 865\u001b[0m )\n\u001b[1;32m 866\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 867\u001b[0m \u001b[39m# Binary mode\u001b[39;00m\n\u001b[1;32m 868\u001b[0m handle \u001b[39m=\u001b[39m \u001b[39mopen\u001b[39m(handle, ioargs\u001b[39m.\u001b[39mmode)\n", "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '2014_World_GDP'" ] } ], "source": [ "df = pd.read_csv('2014_World_GDP')\n", "df.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "linkText": "Export to plot.ly", "plotlyServerURL": "https://plot.ly", "showLink": false }, "data": [ { "colorbar": { "title": { "text": "GDP in Billions USD" } }, "locations": [ "AFG", "ALB", "DZA", "ASM", "AND", "AGO", "AIA", "ATG", "ARG", "ARM", "ABW", "AUS", "AUT", "AZE", "BHM", "BHR", "BGD", "BRB", "BLR", "BEL", "BLZ", "BEN", "BMU", "BTN", "BOL", "BIH", "BWA", "BRA", "VGB", "BRN", "BGR", "BFA", "MMR", "BDI", "CPV", "KHM", "CMR", "CAN", "CYM", "CAF", "TCD", "CHL", "CHN", "COL", "COM", "COD", "COG", "COK", "CRI", "CIV", "HRV", "CUB", "CUW", "CYP", "CZE", "DNK", "DJI", "DMA", "DOM", "ECU", "EGY", "SLV", "GNQ", "ERI", "EST", "ETH", "FLK", "FRO", "FJI", "FIN", "FRA", "PYF", "GAB", "GMB", "GEO", "DEU", "GHA", "GIB", "GRC", "GRL", "GRD", "GUM", "GTM", "GGY", "GNB", "GIN", "GUY", "HTI", "HND", "HKG", "HUN", "ISL", "IND", "IDN", "IRN", "IRQ", "IRL", "IMN", "ISR", "ITA", "JAM", "JPN", "JEY", "JOR", "KAZ", "KEN", "KIR", "KOR", "PRK", "KSV", "KWT", "KGZ", "LAO", "LVA", "LBN", "LSO", "LBR", "LBY", "LIE", "LTU", "LUX", "MAC", "MKD", "MDG", "MWI", "MYS", "MDV", "MLI", "MLT", "MHL", "MRT", "MUS", "MEX", "FSM", "MDA", "MCO", "MNG", "MNE", "MAR", "MOZ", "NAM", "NPL", "NLD", "NCL", "NZL", "NIC", "NGA", "NER", "NIU", "MNP", "NOR", "OMN", "PAK", "PLW", "PAN", "PNG", "PRY", "PER", "PHL", "POL", "PRT", "PRI", "QAT", "ROU", "RUS", "RWA", "KNA", "LCA", "MAF", "SPM", "VCT", "WSM", "SMR", "STP", "SAU", "SEN", "SRB", "SYC", "SLE", "SGP", "SXM", "SVK", "SVN", "SLB", "SOM", "ZAF", "SSD", "ESP", "LKA", "SDN", "SUR", "SWZ", "SWE", "CHE", "SYR", "TWN", "TJK", "TZA", "THA", "TLS", "TGO", "TON", "TTO", "TUN", "TUR", "TKM", "TUV", "UGA", "UKR", "ARE", "GBR", "USA", "URY", "UZB", "VUT", "VEN", "VNM", "VGB", "WBG", "YEM", "ZMB", "ZWE" ], "text": [ "Afghanistan", "Albania", "Algeria", "American Samoa", "Andorra", "Angola", "Anguilla", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia", "Austria", "Azerbaijan", "Bahamas, The", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bermuda", "Bhutan", "Bolivia", "Bosnia and Herzegovina", "Botswana", "Brazil", "British Virgin Islands", "Brunei", "Bulgaria", "Burkina Faso", "Burma", "Burundi", "Cabo Verde", "Cambodia", "Cameroon", "Canada", "Cayman Islands", "Central African Republic", "Chad", "Chile", "China", "Colombia", "Comoros", "Congo, Democratic Republic of the", "Congo, Republic of the", "Cook Islands", "Costa Rica", "Cote d'Ivoire", "Croatia", "Cuba", "Curacao", "Cyprus", "Czech Republic", "Denmark", "Djibouti", "Dominica", "Dominican Republic", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Ethiopia", "Falkland Islands (Islas Malvinas)", "Faroe Islands", "Fiji", "Finland", "France", "French Polynesia", "Gabon", "Gambia, The", "Georgia", "Germany", "Ghana", "Gibraltar", "Greece", "Greenland", "Grenada", "Guam", "Guatemala", "Guernsey", "Guinea-Bissau", "Guinea", "Guyana", "Haiti", "Honduras", "Hong Kong", "Hungary", "Iceland", "India", "Indonesia", "Iran", "Iraq", "Ireland", "Isle of Man", "Israel", "Italy", "Jamaica", "Japan", "Jersey", "Jordan", "Kazakhstan", "Kenya", "Kiribati", "Korea, North", "Korea, South", "Kosovo", "Kuwait", "Kyrgyzstan", "Laos", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Liechtenstein", "Lithuania", "Luxembourg", "Macau", "Macedonia", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Marshall Islands", "Mauritania", "Mauritius", "Mexico", "Micronesia, Federated States of", "Moldova", "Monaco", "Mongolia", "Montenegro", "Morocco", "Mozambique", "Namibia", "Nepal", "Netherlands", "New Caledonia", "New Zealand", "Nicaragua", "Nigeria", "Niger", "Niue", "Northern Mariana Islands", "Norway", "Oman", "Pakistan", "Palau", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Poland", "Portugal", "Puerto Rico", "Qatar", "Romania", "Russia", "Rwanda", "Saint Kitts and Nevis", "Saint Lucia", "Saint Martin", "Saint Pierre and Miquelon", "Saint Vincent and the Grenadines", "Samoa", "San Marino", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Sint Maarten", "Slovakia", "Slovenia", "Solomon Islands", "Somalia", "South Africa", "South Sudan", "Spain", "Sri Lanka", "Sudan", "Suriname", "Swaziland", "Sweden", "Switzerland", "Syria", "Taiwan", "Tajikistan", "Tanzania", "Thailand", "Timor-Leste", "Togo", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Tuvalu", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United States", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela", "Vietnam", "Virgin Islands", "West Bank", "Yemen", "Zambia", "Zimbabwe" ], "type": "choropleth", "z": [ 21.71, 13.4, 227.8, 0.75, 4.8, 131.4, 0.18, 1.24, 536.2, 10.88, 2.52, 1483, 436.1, 77.91, 8.65, 34.05, 186.6, 4.28, 75.25, 527.8, 1.67, 9.24, 5.2, 2.09, 34.08, 19.55, 16.3, 2244, 1.1, 17.43, 55.08, 13.38, 65.29, 3.04, 1.98, 16.9, 32.16, 1794, 2.25, 1.73, 15.84, 264.1, 10360, 400.1, 0.72, 32.67, 14.11, 0.18, 50.46, 33.96, 57.18, 77.15, 5.6, 21.34, 205.6, 347.2, 1.58, 0.51, 64.05, 100.5, 284.9, 25.14, 15.4, 3.87, 26.36, 49.86, 0.16, 2.32, 4.17, 276.3, 2902, 7.15, 20.68, 0.92, 16.13, 3820, 35.48, 1.85, 246.4, 2.16, 0.84, 4.6, 58.3, 2.74, 1.04, 6.77, 3.14, 8.92, 19.37, 292.7, 129.7, 16.2, 2048, 856.1, 402.7, 232.2, 245.8, 4.08, 305, 2129, 13.92, 4770, 5.77, 36.55, 225.6, 62.72, 0.16, 28, 1410, 5.99, 179.3, 7.65, 11.71, 32.82, 47.5, 2.46, 2.07, 49.34, 5.11, 48.72, 63.93, 51.68, 10.92, 11.19, 4.41, 336.9, 2.41, 12.04, 10.57, 0.18, 4.29, 12.72, 1296, 0.34, 7.74, 6.06, 11.73, 4.66, 112.6, 16.59, 13.11, 19.64, 880.4, 11.1, 201, 11.85, 594.3, 8.29, 0.01, 1.23, 511.6, 80.54, 237.5, 0.65, 44.69, 16.1, 31.3, 208.2, 284.6, 552.2, 228.2, 93.52, 212, 199, 2057, 8, 0.81, 1.35, 0.56, 0.22, 0.75, 0.83, 1.86, 0.36, 777.9, 15.88, 42.65, 1.47, 5.41, 307.9, 304.1, 99.75, 49.93, 1.16, 2.37, 341.2, 11.89, 1400, 71.57, 70.03, 5.27, 3.84, 559.1, 679, 64.7, 529.5, 9.16, 36.62, 373.8, 4.51, 4.84, 0.49, 29.63, 49.12, 813.3, 43.5, 0.04, 26.09, 134.9, 416.4, 2848, 17420, 55.6, 63.08, 0.82, 209.2, 187.8, 5.08, 6.64, 45.45, 25.61, 13.74 ] } ], "layout": { "geo": { "projection": { "type": "natural earth" }, "showframe": false }, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "fillpattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "sequentialminus": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "2014 Global GDP" } } }, "text/html": [ "

" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data = dict(\n", " type='choropleth',\n", " locations=df['CODE'],\n", " z=df['GDP (BILLIONS)'],\n", " text=df['COUNTRY'],\n", " colorbar={'title': 'GDP in Billions USD'}\n", ")\n", "\n", "layout = dict(\n", " title='2014 Global GDP',\n", " geo=dict(\n", " showframe=False,\n", " projection={'type': 'natural earth'}\n", " )\n", ")\n", "\n", "choromap3 = go.Figure(data=[data], layout=layout)\n", "iplot(choromap3)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "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": "3.10.6" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }