Can I change value's decimal point seperately in pandas?-CodePudding

I want each values of df have different decimal point like this

        year   month   day 
count   1234   5678    9101
mean    12.12  34.34   2.3456 
std     12.12  3.456   7.789

I searched to find a way to change specific value's decimal point but couldn't find the way. So this is what I've got

        year        month       day 
count   1234.0000   5678.0000   9101.0000
mean    12.1200     34.3400     2.3456 
std     12.1200     3.4560      7.7890

I know the round() method but I don't know how to assign it to each values not the whole row or columns. Is it possible to change values separately?

CodePudding user response：

You can change displayning of floats:

pd.options.display.float_format = '{:,6f}'.format

#if necessary convert to floats
df = df.astype(float)

Or change format to 6 zeros:

df = df.astype(float).applymap('{:.6f}'.format)

CodePudding user response：

The format approach is correct, but I think what you are looking for is this:

Input file data.txt

        year        month       day 
count   1234.0000   5678.0000   9101.0000
mean    12.1200     34.3400     2.3456 
std     12.1200     3.4560      7.7890

Formatting (see formatting mini language)

import numpy as np
import pandas as pd

file = "/path/to/data.txt"
df = pd.read_csv(file, delim_whitespace=True)

# update all columns with data type number
# use the "n" format
df.update(df.select_dtypes(include=np.number).applymap('{:n}'.format))
print(df)

Output

        year  month     day
count   1234   5678    9101
mean   12.12  34.34  2.3456
std    12.12  3.456   7.789