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chevron_left Miscellaneous Cookbook
Adjusting number of rows that are printedAppending DataFrame to an existing CSV fileChecking differences between two indexesChecking if a DataFrame is emptyChecking if a variable is a DataFrameChecking if index is sortedChecking if value exists in IndexChecking memory usage of DataFrameChecking whether a Pandas object is a view or a copyConcatenating a list of DataFramesConverting a DataFrame to a listConverting a DataFrame to a SeriesConverting DataFrame to a list of dictionariesConverting DataFrame to list of tuplesCounting the number of negative valuesCreating a DataFrame using cartesian product of two DataFramesDisplaying DataFrames side by sideDisplaying full non-truncated DataFrame valuesDrawing frequency histogram of DataFrame columnExporting Pandas DataFrame to PostgreSQL tableHighlighting a particular cell of a DataFrameHighlighting DataFrame cell based on valueHow to solve "ValueError: If using all scalar values, you must pass an index"Importing BigQuery table as Pandas DataFramePlotting two columns of DataFramePrinting DataFrame on a single linePrinting DataFrame without indexPrinting DataFrames in tabular formatRandomly splitting DataFrame into multiple DataFrames of equal sizeReducing DataFrame memory sizeSaving a DataFrame as a CSV fileSaving DataFrame as Excel fileSaving DataFrame as feather fileSetting all values to zeroShowing all dtypes without truncationSplitting DataFrame into multiple DataFrames based on valueSplitting DataFrame into smaller equal-sized DataFramesWriting DataFrame to SQLite
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chevron_left Miscellaneous Cookbook
Adjusting number of rows that are printedAppending DataFrame to an existing CSV fileChecking differences between two indexesChecking if a DataFrame is emptyChecking if a variable is a DataFrameChecking if index is sortedChecking if value exists in IndexChecking memory usage of DataFrameChecking whether a Pandas object is a view or a copyConcatenating a list of DataFramesConverting a DataFrame to a listConverting a DataFrame to a SeriesConverting DataFrame to a list of dictionariesConverting DataFrame to list of tuplesCounting the number of negative valuesCreating a DataFrame using cartesian product of two DataFramesDisplaying DataFrames side by sideDisplaying full non-truncated DataFrame valuesDrawing frequency histogram of DataFrame columnExporting Pandas DataFrame to PostgreSQL tableHighlighting a particular cell of a DataFrameHighlighting DataFrame cell based on valueHow to solve "ValueError: If using all scalar values, you must pass an index"Importing BigQuery table as Pandas DataFramePlotting two columns of DataFramePrinting DataFrame on a single linePrinting DataFrame without indexPrinting DataFrames in tabular formatRandomly splitting DataFrame into multiple DataFrames of equal sizeReducing DataFrame memory sizeSaving a DataFrame as a CSV fileSaving DataFrame as Excel fileSaving DataFrame as feather fileSetting all values to zeroShowing all dtypes without truncationSplitting DataFrame into multiple DataFrames based on valueSplitting DataFrame into smaller equal-sized DataFramesWriting DataFrame to SQLite
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Saving Pandas DataFrame as feather file

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Miscellaneous Cookbook
schedule Mar 9, 2022
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Consider the following Pandas DataFrame:

import pandas as pd

df = pd.DataFrame({
"A":[3,4],
"B":[5.0,6.0],
"C":["c","c"],
"D":["d","d"],
"E":[True,False],
"F":pd.date_range("2021-12-25","2021-12-26")})

df["C"] = df["C"].astype("string")
df["D"] = df["D"].astype("category")

dtypes
A int64
B float64
C string
D category
E bool
F datetime64[ns]
dtype: object

To save the DataFrame as a feather file called test.feather in the same directory as this Python script:

df.to_feather("test.feather")

Note that you need to have pyarrow thrown installed - otherwise an error will be thrown. You can use pip to install pyarrow:

pip install pyarrow

To read back the feather file test.feather:

my_df = pd.read_feather("test.feather")
my_df.dtypes
A int64
B float64
C string
D category
E bool
F datetime64[ns]
dtype: object

Notice how the feather file actually preserved the data types of the column - this is something we don't get using csv storage method.

robocat
Published by Isshin Inada
Edited by 0 others
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