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Multiplying all values ​​in Pandas Dataframe rows

It's basically a data file:

      col1    col2    col3    label
row1   1       0       1        1
row2   0       0       0        1
row3   1       1       1        0
row4   1       2       1        0

I basically need it to go down each line, and if label = 0, multiply all the values ​​in the line by -1.

I've tried many different approaches, including:

df.ix[3] = df.ix[3].multiply(-1)

Which returns:

SettingWithCopyWarning: The value is trying to be set on a copy of the slice from the DataFrame. Try using .loc [row_indexer, col_indexer] =

I also tried deleting the row and replacing, which doesn't work because the indices are changing.

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3 answers


Alternatively, you can run apply

for row operations:



df = df.apply(lambda row: row*-1 if row['label'] == 0 else row, axis=1)

print(df)    
#       col1  col2  col3  label
# row1     1     0     1      1
# row2     0     0     0      1
# row3    -1    -1    -1      0
# row4    -1    -2    -1      0
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In [156]: df.loc[df.label==0, df.columns.drop('label')] = \
              df.loc[df.label==0, df.columns.drop('label')].mul(-1)

In [157]: df
Out[157]:
      col1  col2  col3  label
row1     1     0     1      1
row2     0     0     0      1
row3    -1    -1    -1      0
row4    -1    -2    -1      0

or a shorter version:



In [160]: df.loc[df.label==0, df.columns.drop('label')] *= -1

In [161]: df
Out[161]:
      col1  col2  col3  label
row1     1     0     1      1
row2     0     0     0      1
row3    -1    -1    -1      0
row4    -1    -2    -1      0
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One approach using broadcasting

and masking

mainly exploiting the fact that multiplication 0

by -1

will not change 0

so that we can multiply all strings by -1

that have corresponding values label

like 0s

-

df[(df.label==0)] *= -1

Example run -

In [70]: df
Out[70]: 
      col1  col2  col3  col4  label
row1     1     0     1     3      1
row2     0     0     0     2      1
row3     1     1     1     5      0
row4     1     2     1     7      0

In [71]: df[(df.label==0)] *= -1

In [72]: df
Out[72]: 
      col1  col2  col3  col4  label
row1     1     0     1     3      1
row2     0     0     0     2      1
row3    -1    -1    -1    -5      0
row4    -1    -2    -1    -7      0
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