CODEWITHSUNDEEP
pythonpandas
Eliza
Eliza

Reputation: 33

How to make two dataframes one with values and another with boolean into one dataframe in python?

For example, I have two dataframes like:

dataframe1 would be

            A     B     C     D     E
values1  0.25  0.33  0.12  0.22  0.08
values2  0.20  0.50  0.89  0.65  0.75

and dataframe2 would be

              A     B     C      D     E
boolean1   True False  True  False  True
boolean2  False False  True   True  True

and want a result with one dataframe:

      A  B     C     D     E
1  0.25  0  0.12     0  0.08  
2     0  0  0.89  0.65  0.78

So if it is True in dataframe2 just bring the value from the dataframe1 and if it is False then replace with 0. How can I do this?

Upvotes: 3

Views: 146

Answers (3)

Himanshu Poddar
Himanshu Poddar

Reputation: 7789

You can use pandas.DataFrame.mask if its guaranteed that both dataframe will always be of same shape.

creating the data

df1 = pd.DataFrame([['values1', '0.25', '0.33', '0.12', '0.22', '0.08'], ['values2', '0.20', '0.50', '0.89', '0.65', '0.75']], columns = ['index', 'A', 'B', 'C', 'D', 'E']).set_index('index')

df2 = pd.DataFrame([['boolean1', True, False,  True,  False,  True], ['boolean2',  False, False,  True,   True,  True]], columns = ['index', 'A', 'B', 'C', 'D', 'E']).set_index('index')

Mask

df1.mask(~df2.values, 0)

Output

This gives us

            A  B     C     D     E
index                             
values1  0.25  0  0.12     0  0.08
values2     0  0  0.89  0.65  0.75

Upvotes: 0

ThePyGuy
ThePyGuy

Reputation: 18426

One way is to just multiply the values in the dataframe, then create the dataframe out of it.

>>> out = pd.DataFrame(df1.values * df2.values, columns=df1.columns)

OUTPUT

      A    B     C     D     E
0  0.25  0.0  0.12  0.00  0.08
1  0.00  0.0  0.89  0.65  0.75

Or you can just multiply the dataframes dropping the indices:

>>> df1.reset_index(drop=True)*df2.reset_index(drop=True)

      A    B     C     D     E
0  0.25  0.0  0.12  0.00  0.08
1  0.00  0.0  0.89  0.65  0.75

Upvotes: 1

Ynjxsjmh
Ynjxsjmh

Reputation: 30032

You can use

df1 = df1.where(df2.values, 0)
# or
df1 = df1.mask(~df2.values, 0)

print(df1)

            A    B     C     D     E
values1  0.25  0.0  0.12  0.00  0.08
values2  0.00  0.0  0.89  0.65  0.75

Upvotes: 2

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