map and format: Insert a String into a Pandas series
If you want to insert a string into all values of a pandas Series, use pandas map and format.
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Pandas
df.filter: Filter Columns Based on a Subset of Their Names
If you want to filter columns of a pandas DataFrame based on characters in their names, use DataFrame.filter. In the example above, we only choose the columns that contain the word “cat”.
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pandas.qcut: Bin a DataFrame’s Values into Equal-Sized Intervals
If you want to bin a column’s values into intervals that contain roughly the same number of elements, use pandas.qcut.
In the example below, the values of “a” are separated into 3 intervals, each of which contains 2 elements.
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to_markdown: Print a DataFrame in Markdown Format
Sometimes, you might want to include a table in a markdown, such as GitHub README. If you want to print a DataFrame in markdown format, use to_markdown().
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Group DataFrame’s Rows into a List Using groupby
It is common to use groupby to get the statistics of rows in the same group such as count, mean, median, etc. If you want to group rows into a list instead, use lambda x: list(x).
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Logging in Pandas Pipelines
When using pandas pipe, you might want to check whether each pipeline transforms your pandas DataFrame correctly.
To automatically log the information of a pandas DataFrame after each pipeline, use the decorator sklego’s log_step.
Find more ways to customize your logging here.
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DataFrame.copy(): Make a Copy of a DataFrame
Have you ever tried to make a copy of a DataFrame using =? You will not get a copy but a reference to the original DataFrame. Thus, changing the new DataFrame will also change the original DataFrame.
A better way to make a copy is to use df.copy(). Now, changing the copy will not affect the original DataFrame.
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df.merge: Merge DataFrame Based on Columns
If you want to merge on DataFrame with another DataFrame based on the similarity between 2 columns, use df.merge.
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size: Compute the Size of Each Group
If you want to get the count of elements in one column of a pandas DataFrame, use groupby and count.
If you want to get the size of groups composed of 2 or more columns, use groupby and size instead.
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pandas.DataFrame.corrwith: Compute Pairwise Correlation Between 2 DataFrame
If you want to compute between rows or columns of two DataFrame, use corrwith.
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