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 chart_otly as py import aph_objects as go import pandas as pd # mapbox_access_token = 'ADD YOUR TOKEN HERE' df = pd. See examples of statistic, scientific, 3D charts, and more here. Plotly: a graphing library for making interactive, publication-quality graphs.SciPy: a Python-based ecosystem of packages for math, science, and engineering.
NumPy: a package for scientific computing with tools for algebra, random number generation, integrating with databases, and managing data.Pandas: import data via a url and create a dataframe to easily handle data for analysis and graphing.Some useful packages that we'll use in this tutorial include: You can reload all changed modules before executing a new line. IPython comes with automatic reloading magic. You may want to reload submodules if you've edited the code in one.
IPYNB VIEWER BROWSER INSTALL
When installing packages in Jupyter, you either need to install the package in your actual shell, or run the ! prefix, e.g.: !pip install packagename Skip down to the for more information on using IRkernel with Jupyter notebooks and graphing examples. You can also use Jupyter notebooks to execute R code. The bulk of this tutorial discusses executing python code in Jupyter notebooks.
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