How can the precision be varied across different columns in pandas?

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One way to vary the precision of different columns in a pandas DataFrame is to use the "round" method with the "decimals" parameter, which allows you to specify the number of decimal places to round to. Here's an example:

import pandas as pd

# create a sample DataFrame with two columns
df = pd.DataFrame({'A': [0.123456789, 1.23456789, 12.3456789],
                   'B': [0.987654321, 9.87654321, 98.7654321]})

# round the 'A' column to 2 decimal places and the 'B' column to 4 decimal places
df_rounded = df.round({'A': 2, 'B': 4})

print(df_rounded)

This will output:

       A       B
0   0.12  0.9877
1   1.23  9.8765
2  12.35 98.7654

Note that you can also pass a single integer value to the "round" method to round all columns to the same number of decimal places. For example, df.round(2) would round all columns to 2 decimal places.