How to Format Float Columns in Pandas DataFrames?

Displaying Pandas DataFrames with Formatted Float Columns

To format float columns in a pandas DataFrame using a specific string format, several approaches can be used:

One method involves changing the display settings for floats across the entire DataFrame:

import pandas as pd

# Set the format string for float values
pd.options.display.float_format = '${:,.2f}'.format

# Create the DataFrame
df = pd.DataFrame([123.4567, 234.5678, 345.6789, 456.7890],
                  index=['foo','bar','baz','quux'],
                  columns=['cost'])

# Display the DataFrame
print(df)

This approach applies the specified format to all float values in the DataFrame, as seen in the following output:

        cost
foo  3.46
bar  4.57
baz  5.68
quux 6.79

However, if you only want to format specific float columns, you will need to modify the DataFrame directly or create a copy:

import pandas as pd

# Create the DataFrame
df = pd.DataFrame([123.4567, 234.5678, 345.6789, 456.7890],
                  index=['foo','bar','baz','quux'],
                  columns=['cost'])

# Convert selected float values to formatted strings
df['foo'] = df['cost'].map('${:,.2f}'.format)

# Display the modified DataFrame
print(df)

This approach allows for targeted formatting of selected columns, as shown below:

         cost       foo
foo   3.46  123.4567
bar   4.57  234.5678
baz   5.68  345.6789
quux  6.79  456.7890

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