How can I left justify text in a pandas DataFrame column in an IPython notebook

Question

I am trying to format the output in an IPython notebook. I tried using the to_string function, and this neatly lets me eliminate the index column. But the textual data is right justified.

In [10]:

import pandas as pd
columns = ['Text', 'Value']
a = pd.DataFrame ({'Text': ['abcdef', 'x'], 'Value': [12.34, 4.2]})
print (a.to_string (index=False))

   Text  Value
 abcdef  12.34
      x   4.20

The same is true when just printing the dataframe.

In [12]:

print (a)

     Text  Value
0  abcdef  12.34
1       x   4.20

The justify argument in the to_string function, surprisingly, only justifies the column heading.

In [13]:

import pandas as pd
columns = ['Text', 'Value']
a = pd.DataFrame ({'Text': ['abcdef', 'x'], 'Value': [12.34, 4.2]})
print (a.to_string (justify='left', index=False))
Text     Value
 abcdef  12.34
      x   4.20

How can I control the justification settings for individual columns?

Answer 1

If you're willing to use another library, tabulate will do this -

$ pip install tabulate

and then

from tabulate import tabulate
df = pd.DataFrame ({'Text': ['abcdef', 'x'], 'Value': [12.34, 4.2]})
print(tabulate(df, showindex=False, headers=df.columns))

Text      Value
------  -------
abcdef    12.34
x          4.2

It has various other output formats also.

Answer 2

You could use a['Text'].str.len().max() to compute the length of the longest string in a['Text'], and use that number, N, in a left-justified formatter '{:<Ns}'.format:

In [211]: print(a.to_string(formatters={'Text':'{{:<{}s}}'.format(a['Text'].str.len().max()).format}, index=False))
   Text  Value
 abcdef  12.34
 x        4.20

Answer 3

I like @unutbu's answer (not requiring any additional dependencies). @JS.'s additions are a step in the direction (towards something re-usable).

Since the construction of the formatter dict is the difficult part, let's create a function which creates the formatter dict from a DataFrame and an optional list of columns to format.

def make_lalign_formatter(df, cols=None):
    """
    Construct formatter dict to left-align columns.

    Parameters
    ----------
    df : pandas.core.frame.DataFrame
        The DataFrame to format
    cols : None or iterable of strings, optional
        The columns of df to left-align. The default, cols=None, will
        left-align all the columns of dtype object

    Returns
    -------
    dict
        Formatter dictionary

    """
    if cols is None:
       cols = df.columns[df.dtypes == 'object'] 

    return {col: f'{{:<{df[col].str.len().max()}s}}'.format for col in cols}

Let's create some example data to demonstrate using this function:

import pandas as pd

# Make some data
data = {'First': ['Tom', 'Dick', 'Harry'],
        'Last': ['Thumb', 'Whittington', 'Potter'],
        'Age': [183, 667, 23]}

# Make into a DataFrame
df = pd.DataFrame(data)

To align all the columns of type object in our DataFrame:

# Left align all columns
print(df.to_string(formatters=make_lalign_formatter(df), 
                   index=False,
                   justify='left'))

To align only the 'First' column:

# Left align 'First' column
print(df.to_string(formatters=make_lalign_formatter(df, cols=['First']), 
                   index=False,
                   justify='left'))