Format certain floating dataframe columns into percentage in pandas
I am trying to write a paper in IPython notebook, but encountered some issues with display format. Say I have following dataframe df
, is there any way to format var1
and var2
into 2 digit decimals and var3
into percentages.
var1 var2 var3
id
0 1.458315 1.500092 -0.005709
1 1.576704 1.608445 -0.005122
2 1.629253 1.652577 -0.004754
3 1.669331 1.685456 -0.003525
4 1.705139 1.712096 -0.003134
5 1.740447 1.741961 -0.001223
6 1.775980 1.770801 -0.001723
7 1.812037 1.799327 -0.002013
8 1.853130 1.822982 -0.001396
9 1.943985 1.868401 0.005732
The numbers inside are not multiplied by 100, e.g. -0.0057=-0.57%.
The accepted answer suggests to modify the raw data for presentation purposes, something you generally do not want. Imagine you need to make further analyses with these columns and you need the precision you lost with rounding.
You can modify the formatting of individual columns in data frames, in your case:
output = df.to_string(formatters={
'var1': '{:,.2f}'.format,
'var2': '{:,.2f}'.format,
'var3': '{:,.2%}'.format
})
print(output)
For your information '{:,.2%}'.format(0.214)
yields 21.40%
, so no need for multiplying by 100.
You don't have a nice HTML table anymore but a text representation. If you need to stay with HTML use the to_html
function instead.
from IPython.core.display import display, HTML
output = df.to_html(formatters={
'var1': '{:,.2f}'.format,
'var2': '{:,.2f}'.format,
'var3': '{:,.2%}'.format
})
display(HTML(output))
Update
As of pandas 0.17.1, life got easier and we can get a beautiful html table right away:
df.style.format({
'var1': '{:,.2f}'.format,
'var2': '{:,.2f}'.format,
'var3': '{:,.2%}'.format,
})
You could also set the default format for float :
pd.options.display.float_format = '{:.2%}'.format
Use '{:.2%}' instead of '{:.2f}%' - The former converts 0.41 to 41.00% (correctly), the latter to 0.41% (incorrectly)