问题
I have a dataframe -
year month type amount
0 2019 9 Not Applicable 8000.00
1 2019 10 Not Applicable 7500.00
2 2019 11 Goods & Services 14000.35
3 2019 11 Not Applicable 7500.00
4 2019 12 Goods & Services 10499.00
5 2019 12 Not Applicable 9801.00
I have column amount fully round of but I want to convert another column month to this format like this -
year month type amount
0 2019 9.00 Not Applicable 8000.00
1 2019 10.00 Not Applicable 7500.00
2 2019 11.00 Goods & Services 14000.35
3 2019 11.00 Not Applicable 7500.00
4 2019 12.00 Goods & Services 10499.00
5 2019 12.00 Not Applicable 9801.00
How can I achieve this thing.
回答1:
df.month = df.month.astype(float)
or
df['month'] = df['month'].astype(float)
回答2:
To convert into float with 2 decimal places :
df['month'] = df['month'].astype('float').map('{:,.2f}'.format)
df['month']
Output :
0 9.00
1 10.00
2 11.00
3 11.00
4 12.00
5 12.00
回答3:
Terminology is key here. If you just want to change the "format" within your jupyter notebook -- which has no impact when sent to excel -- then @SurajSubramanian 's answer should be the accepted solution. If you simply want to change the column to float format, then @nav610 's answer is correct, but the title of your question is specifically "Change int value to .00 format"
So, I mentioned, terminology is key, because if you acutally want to change the underlying value to end with .00, then your only option is to convert it to a string like so:
df['month'] = df['month'].astype(str) + '.00'
year month type amount
0 2019 9.00 Not Applicable 8000.00
1 2019 10.00 Not Applicable 7500.00
2 2019 11.00 Goods & Services 14000.35
3 2019 11.00 Not Applicable 7500.00
4 2019 12.00 Goods & Services 10499.00
5 2019 12.00 Not Applicable 9801.00
See my comments on some of the answers for more context, but the answer is that it really depends on your actual use case what the best solution is.
来源：https://stackoverflow.com/questions/62846784/change-int-value-to-00-format