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In programming, even small tips or tools can make a big difference.
For example, a shortcut key or a helpful package might simplify a lot of work and double your efficiency.
Here I’ll share a few small tricks I often use.
pandas_profiling to Inspect DataFramesUnderstanding your data is essential before doing any analysis.
Although df.describe() and df.info() provide basic summaries, they’re limited with large or complex datasets.
The pandas_profiling library offers detailed profiling through profile_report().
pip install pandas-profiling
# or
conda install -c anaconda pandas-profiling
It’s very easy to use:
import pandas as pd
import pandas_profiling
df = pd.read_csv("train.csv")
df.profile_report()
You can also export the report to HTML:
html = df.profile_report(title='Titanic Profiling Report')
html.to_file(outputfile="titanic_Profiling_Report.html")
cufflinksPandas has built-in plotting via .plot(), but it’s not interactive.
If you want interactivity, try the cufflinks package.