Pandas
keyboard_arrow_down 655 guides
chevron_leftMiscellaneous 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
check_circle
Mark as learned thumb_up
3
thumb_down
0
chat_bubble_outline
0
Comment auto_stories Bi-column layout
settings
Displaying DataFrames side by side in Pandas
schedule Aug 12, 2023
Last updated local_offer
Tags Python●Pandas
tocTable of Contents
expand_more Master the mathematics behind data science with 100+ top-tier guides
Start your free 7-days trial now!
Start your free 7-days trial now!
To display multiple DataFrames side by side:
from IPython.display import display_html
df1 = pd.DataFrame({"A":[2,3],"B":[4,5]})df2 = pd.DataFrame({"A":[6,7],"B":[8,9]})
df1_style = df1.style.set_table_attributes("style='display:inline; margin-right:20px;'").set_caption("DF One")df2_style = df2.style.set_table_attributes("style='display:inline'").set_caption("DF Two")
display_html(df1_style._repr_html_() + df2_style._repr_html_(), raw=True)
DF One DF Two A B A B0 2 4 0 6 81 3 5 1 7 9
Note the following:
we use CSS to style the output of the DataFrames. The
display:inline
is what allows the DataFrames to be printed on the same line._repr_html()
returns the raw string (HTML
) representation of the DataFrame with the styling you specified.raw=True
must be set for the DataFrames to be printed sincedisplay_html(~)
does not print out raw strings by default.
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
thumb_up
thumb_down
Comment
Citation
Ask a question or leave a feedback...
thumb_up
3
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!