Change the print format of a series while keeping the dtype the same

Rob Lasch 0
Viewed 11

I am trying to change the output format of columns in a dataframe without changing the data types.

import pandas as pd
df = pd.DataFrame({'name': ['Johnny', 'Brad'], 
                   'rate': [0.02, 0.035],
                   'wage': [50000.0, 35000.0]})
print(df.dtypes)
df

which results in the following output

name     object
rate    float64
wage    float64
dtype: object
name    rate    wage
0   Johnny  0.020   50000.0
1   Brad    0.035   35000.0

I am trying to change the formats without changing the datatypes

df['rate'] = df['rate'].astype(float).map("{:.2%}".format)
df['wage'] = df.apply(lambda x: "{:,}".format(x['wage']), axis=1)

print(df.dtypes)
df

Unfortunately the result is this

name    object
rate    object
wage    object
dtype: object
name    rate    wage
0   Johnny  2.00%   50,000.0
1   Brad    3.50%   35,000.0

So now if I try to do calculations, they fail. For Example:

df['wage'].sum()

Produces this result

'50,000.035,000.0'

How do I change the print formats, but keep the dtypes as floats?

format dataframe pandas python
1 Answers

You want display only, so do not change the df (assign the value back)

print(df.to_string(formatters={'rate': '{:.2%}'.format, 'wage':'{:,}'.format}))
     name  rate     wage
0  Johnny 2.00% 50,000.0
1    Brad 3.50% 35,000.0
#df['wage'].sum()
#Out[124]: 85000.0
BENY0
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