My apologies beforehand! I have done this before a few times, but I am having some brain fog. I have two dataframes df1, and df2. I would like to update all values in df2 if it matches a specific value in df1, while not changing the other values in df2. I can do this pretty easily with np.where on columns of a dataframe, I am having brain fog on how I did this previously with 2 dataframes!
Goal: Set values in Df2 to 0 if they are 0 in DF1 - otherwise keep the DF2 value
Example
df1
| A | B | C |
|---|---|---|
| 4 | 0 | 1 |
| 0 | 2 | 0 |
| 1 | 4 | 0 |
df2
| A | B | C |
|---|---|---|
| 1 | 8 | 1 |
| 9 | 2 | 7 |
| 1 | 4 | 6 |
Expected df2 after our element swap
| A | B | C |
|---|---|---|
| 1 | 0 | 1 |
| 0 | 2 | 0 |
| 1 | 4 | 0 |
brain fog is bad! thank you for the assistance!
CodePudding user response：
Using fillna
>>> df2[df1 != 0].fillna(0)
CodePudding user response：
You can try
df2[df1.eq(0)] = 0
print(df2)
A B C
0 1 0 1
1 0 2 0
2 1 4 0
CodePudding user response：
You can use a boolean mask, but only if you are sure that your dataframes have the same shape:
for col in df1.columns:
mask = df1[df1[col] == 0]
df2.loc[mask, col] = 0