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Working with Python’s pandas library often?
This resource will be worth its length in gold!
Kevin Markham shares his tips and tricks for the most common data handling tasks on twitter. He compiled the top 100 in this one amazing overview page. Find the hyperlinks to specific sections below!
pandas trick: Want to plot a DataFrame? It's as easy as:
df.plot(kind='…')You can use:
line
bar
barh
hist
box
kde
area
scatter
hexbin
pieOther plot types are available via pd.plotting!
Examples: https://t.co/fXYtPeVpZX#Python #dataviz #pandastricks pic.twitter.com/kp82wA15S4
— Kevin Markham (@justmarkham) August 23, 2019
Quicklinks to categories
- Reading files
- Reading from the web
- Creating example DataFrames
- Creating columns
- Renaming columns
- Selecting rows and columns
- Filtering rows by condition
- Manipulating strings
- Working with data types
- Encoding data
- Extracting data from lists
- Working with time series data
- Handling missing values
- Using aggregation functions
- Using cumulative functions
- Random sampling
- Merging DataFrames
- Styling DataFrames
- Exploring a dataset
- Handling warnings
- Other
Kevin even made a video demonstrating his 25 most useful tricks:
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