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I also assume that you have Anaconda installed, or know how to install packages into Python. Figure ( data = data, layout = layout ) py. Reading and plotting data in Jupyter notebook For this tutorial I am going to assume that you have some idea about using either Jupyter notebook or Python in general. Here is a link to a helpful site about using markdown (used for the text cells in Jupyter notebook) and LaTeX in Jupyter notebooks by Khelifi Ahmed Aziz. It is possible to include subscripts and Greek letters in matplotlib figure labels using LaTeX. Surface ( x = x, y = y, z = z ) data = layout = go. Next we will use functions for matplotlib.pyplot to add labels for each axis. Now let’s look at another example of a statistical transformation.
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cos ( tGrid ) # z = r*cos(t) surface = go. In this section, you’ll learn more about the three required components for creating a data visualization using plotnine. sin ( tGrid ) # y = r*sin(s)*sin(t) z = r * np. sin ( tGrid ) # x = r*cos(s)*sin(t) y = r * np. sin ( 7 * sGrid + 5 * tGrid ) # r = 2 + sin(7s+5t) x = r * np. Import otly as py import aph_objs as go import numpy as np s = np. iplot ( fig, filename = 'jupyter-Nuclear Waste Sites on American Campuses' ) Layout ( title = 'Nuclear Waste Sites on Campus', autosize = True, hovermode = 'closest', showlegend = False, mapbox = dict ( accesstoken = mapbox_access_token, bearing = 0, center = dict ( lat = 38, lon =- 94 ), pitch = 0, zoom = 3, style = 'light' ), ) fig = dict ( data = data, layout = layout ) py. read_csv ( ' %20o n%20American%20Campuses.csv' ) site_lat = df. Import otly as py import aph_objs as go import pandas as pd # mapbox_access_token = 'ADD YOUR TOKEN HERE' df = pd.