Replace values in dataframe from another dataframe ? #pandas

replace_pandas.py

1. Substitute the NaN's in a dataframe with values from another dataframe

If you have two DataFrames of the same shape, then:

df[df.isnull()] = d2



2.Replace values in a dataframe with values from another dataframe by conditions

DataFrame.mask()

A = B.mask(condition, A)
When condition is true, the values from A will be used, otherwise B's values will be used.


3.


Is there a way to merge the values from one dataframe onto another without getting the _X, _Y columns? I'd like the values on one column to replace all zero values of another column.

df1: 

Name   Nonprofit    Business    Education

X      1             1           0
Y      0             1           0   <- Y and Z have zero values for Nonprofit and Educ
Z      0             0           0
Y      0             1           0

df2:

Name   Nonprofit    Education
Y       1            1     <- this df has the correct values. 
Z       1            1


-----------------------

df.loc[df.Name.isin(df1.Name), ['Nonprofit', 'Education']] = df1[['Nonprofit', 'Education']]
df
Out[27]:
  Name  Nonprofit  Business  Education
0    X          1         1          0
1    Y          1         1          1
2    Z          1         0          1
3    Y          1         1          1

[4 rows x 4 columns]