Wrapping column names in Python Pandas DataFrame or Jupyter Notebooks

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I have long titles for some of my columns in my data frame, and I would like the ability to wrap the text. I know that this functionality is built into pandas, as I do:

pd.DataFrame(np.random.randn(2, 10), 
    columns=['Very Long Column Title ' + str(i) for i in range(10)])

DataFrame with wrapped column names

But if I have fewer columns, the titles will not wrap:

pd.DataFrame(np.random.randn(10, 2), 
    columns=['Very Long Column Title ' + str(i) for i in range(2)])

DataFrame does not wrap column names

I have also tried to manually insert a newline:

import pandas as pd    
pd.DataFrame(np.random.randn(10, 2), 
    columns=['Very Long \n Column Title ' + str(i) for i in range(2)])

But that gives the same output as above.

I've found similar for answers on this topic:

  • Can I set variable column widths in pandas? will truncate column widths, but will not affect the title and will not wrap the text
  • Pretty printing newlines inside a string in a Pandas DataFrame This again touches on column contents but not the title

I am working in a Jupyter notebook, but would prefer a pandas-based solution, if possible.

Here is an answer that does not involve changing the IPython properties:

df = pd.DataFrame(np.random.randn(10, 2), 
    columns=['Very Long Column Title ' + str(i) for i in range(2)])
df.style.set_table_styles([dict(selector="th",props=[('max-width', '50px')])])

How to print an entire pandas DataFrame in Python, Jupyter notebooks inherit their display properties from a number of sources. There is no property in pandas that restricts the width of the column  A problem with this technique of renaming columns is that one has to change names of all the columns in the Dataframe. This approach would not work if we want to change the name of just one column. The rename method outlined below is more versatile and works for renaming all columns or just specific ones.

Jupyter notebooks inherit their display properties from a number of sources. There is no property in pandas that restricts the width of the column headers because pandas is not what causes the text to wrap, it is actually the rendered HTML.

You can overwrite the default Jupyter Notebook styles to restrict the maximum width of the table headers using:

from IPython.core.display import HTML
HTML("<style>.rendered_html th {max-width: 120px;}</style>")

Run this code once at the top of your notebook to set the max column width of html table headers to 120 pixels.

Pretty displaying tricks for columnar data in Python, How do I find the number of rows and columns in Python? Data after removing max column limit End of the day.. If you are comfortable frequently using Jupyter notebooks, simply setting max columns to None will display all of your data at once. But if you are a person who likes to write code in editors and not move to Jupyter notebooks to understand data, using the tabulate library is the best way to go.

Alternatively, you could use the package textwrap:

import textwrap

cols = ['Very Long Column Title ' + str(i) for i in range(2)]

# Split wide columns, you can then join these with any delimiter you'd like
cols = [textwrap.wrap(x, width=20) for x in cols]

# print(cols)
# [['Very Long Column', 'Title 0'], ['Very Long Column', 'Title 1']]

Options and settings, For everyone who has extensively wrangled data using lists, Pandas, It is as easy as wrapping a simple function to the print function used on pdtabulate=​lambda df:tabulate(df,headers='keys') If you are comfortable frequently using Jupyter notebooks, simply setting max columns to None will display  I know this question is a little old but the following worked for me in a Jupyter Notebook running pandas 0.22.0 and Python 3: import pandas as pd pd.set_option('display.max_columns', <number of columns>) You can do the same for the rows too: pd.set_option('display.max_rows', <number of rows>)

You can "hack in" the correct behavior by inserting spaces into column headings with:

def colfix(df, L=5): return df.rename(columns=lambda x: ' '.join(x.replace('_', ' ')[i:i+L] for i in range(0,len(x),L)) if df[x].dtype in ['float64','int64'] else x )

colfix(your_df)

See my answer to a similar question https://stackoverflow.com/a/45078833/6903458

DataFrame.style, The following will not work because it matches multiple option names, e.g. Using startup scripts for the Python/IPython environment to import pandas and set of dataframes to stretch across pages, wrapped over the full column vs row-​wise. When True, Jupyter notebook will process table contents using MathJax,​  The following will change the name of the 'Book Value' column to 'BookValue', removing the space and allowing access to that column's data using property notation. Using .rename() in this manner returns a new data frame with the columns renamed and the data copied from the original.

pandas.set_option, This document is written as a Jupyter Notebook, and can be viewed or Styler.​apply passes each column or row into your DataFrame one-at-a-time or the entire or axis keyword argument, consider wrapping your function in a functools.​partial Series([-10,-5,0,90], name='Both Pos and Neg') head = """ <table> <​thead>  Date Sun 05 March 2017 Tags python / jupyter In [1]: # pip3 install pandas openpyxl import pandas csv_file = "queries.csv" queries_dataframe = pandas . read_csv ( csv_file ) queries_dataframe . head ()

Column edit jupyter, [escape, longtable, multicolumn, multicolumn_format, multirow, repr]; display. but unless you use the full option name (e.g. x.y.z.option_name), your code may will wrap-around across multiple “pages” if its width exceeds display.width . The IPython notebook, IPython qtconsole, or IDLE do not run in a terminal and  I've got several columns with long strings of text in a pandas data frame, but am only interested in examining one of them. Is there a way to use something along the lines of pd.set_option('max_colwidth', 60) but for a single column only, rather than expanding the width of all the columns in my df?

Pandas 100 tricks, Dec 20, 2017 · Rename multiple pandas dataframe column names. Anaconda. assigning a new column the already existing dataframe in python pandas is Jupyter's Notebooks and dashboard are web apps, and Jupyter starts up a local of dataframes to stretch across pages, wrapped over the full column vs row-​wise. The last two libraries will allow us to create web base notebooks in which we can play with python and pandas. If you don’t know what jupyter notebooks are you can see this tutorial. Next, we need to start jupyter. I find it useful to store all notebooks on a cloud storage or a folder under version control, so I can share between multiple

Comments
  • Thanks! A native pandas result, which is what I had hoped for.
  • This solution only works in jupyter, not when used outside of a notebook.
  • thank you - thank you - thank you. This works very nicely with other pandas.style features.
  • Perfect! I knew this had to be a setting somewhere, but couldn't figure out where.