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Powerful visualizations, and an easy to use, interactive api for exploring and loading datasets
Must have python 3.9+
pip install chart-tools
import chart_tools as ct
ct.load_data() # outputs available pre-defined data sources
load_data()
function and DataSource
object use Github's API to explore file structures in repositories containing .csv
files, and easily load files into dataframes. Chart-tools has a pre-defined library (collection of repositories) for you to explore within your notebook and load data from.df_raw = ...
and then use df = df_raw.copy()
to get your original data again.superheat
FAQs
Powerful visualizations, and an easy to use, interactive api for exploring and loading datasets
We found that chart-tools demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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