Here was what I'm working on
df_top_50= df[['Rank', 'Player', 'Position', 'Age', 'Nationality', 'Club Left', 'Club Joined', 'Transfer Fee (EUR)']]
It returned
Rank Player Position Age Nationality Club Left Club Joined Transfer Fee (EUR)
1 1 Antony Forward 22 Netherlands Ajax Amsterdam Manchester United 95.00
2 2 Wesley Fofana Defender 21 England Leicester City Chelsea FC 80.40
3 3 Aurélien Tchouameni Midfielder 22 Monaco AS Monaco Real Madrid 80.00
I wanna get rid of the index column, so I add style.hide_index()
:
df_top_50= df[['Rank', 'Player', 'Position', 'Age', 'Nationality', 'Club Left', 'Club Joined', 'Transfer Fee (EUR)']].style.hide_index()
I got what I want, but the values in transfer fee column suddenly added 0s after decimal:
Rank Player Position Age Nationality Club Left Club Joined Transfer Fee (EUR)
1 Antony Forward 22 Netherlands Ajax Amsterdam Manchester United 95.000000
2 Wesley Fofana Defender 21 England Leicester City Chelsea FC 80.400000
3 Aurélien Tchouameni Midfielder 22 Monaco AS Monaco Real Madrid 80.000000
Is there any way to put it back, like in the first dataframe?
If OP's goal is to round the values in the column Transfer Fee (EUR)
, one can use pandas.DataFrame.round
as
df = df.round({'Transfer Fee (EUR)': 1})
Then the values of that column will be
0 95.0
1 80.4
2 80.0
Alternatively, if OP wants to specify the exact number of decimal places, assuming one wants that number to be 2
, then one can use pandas.DataFrame.apply
as follows
df['Transfer Fee (EUR)'] = df['Transfer Fee (EUR)'].apply('{0:.2f}'.format)
Then the values of that column will be
0 95.00
1 80.40
2 80.00
Since pandas.io.formats.style.Styler.hide_index
is deprecated, use pandas.io.formats.style.Styler.hide
instead.
Deprecated since version 1.4.0 : This method should be replaced by hide(axis="index", **kwargs)
Try this:
df.style.format({'Transfer Fee (EUR)': "{:.2f}"}).hide()
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