Create a new DataFrame from two existing DataFrames

Question

I am a pandas rookie and I have reviewed similar questions in stackoverflow, but this seems unique.

I am looking for a function that will compare A and B and if any column in B has a value > 0 for the column, the DataFrame B will be used to create DataFrame C.

The goal is for DataFrame C the same size as DataFrame A, just with DataFrame B's values for the columns with the same label.

Have: 
A = pd.DataFrame({"X1": [0], "Y1": [0], "X2": [0], "Y2": [0], "X3": [0], "Y3": [0], "X4": [0], "Y4": [0]})

B = pd.DataFrame({"X1": [9], "Y1": [99.9]})

Want:

C= pd.DataFrame({"X1": [9], "Y1": [99.9], "X2": [0], "Y2": [0], "X3": [0], "Y3": [0], "X4": [0], "Y4": [0]})

So will DataFrame A always have only 0 as values, as your example seems to suggest ? — manu190466
– manu190466, Commented Dec 2, 2020 at 22:05
Can B contain keys not in A? Can you just for b in B: or would that have illegal values? — Larry OBrien
– Larry OBrien, Commented Dec 2, 2020 at 22:05

Cainã Max Couto da Silva · Accepted Answer · 2020-12-02 22:56:57Z

2

You can use pandas update where B > 0:

C = A.copy()
C.update(B.where(B>0))

Output:

   X1    Y1  X2  Y2  X3  Y3  X4  Y4
0   9  99.9   0   0   0   0   0   0

edited Dec 2, 2020 at 22:56

answered Dec 2, 2020 at 22:49

Cainã Max Couto da Silva

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1 Comment

SDM1212 Over a year ago

That's a great solution!

SDM1212 · Accepted Answer · 2020-12-02 21:58:01Z

1

I have a solution but is seems a bit forced

import pandas as pd


A = pd.DataFrame({"X1": [0], "Y1": [0], "X2": [0], "Y2": [
                 0], "X3": [0], "Y3": [0], "X4": [0], "Y4": [0]})

B = pd.DataFrame({"X1": [9], "Y1": [99.9]})

C = pd.concat([A, B])

D = C.fillna(0)

E = D.iloc[1:]

print (E)

Ideas are welcome!

answered Dec 2, 2020 at 21:58

SDM1212

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Comments

fthomson · Accepted Answer · 2020-12-02 23:04:30Z

1

It's a little ugly but it gets the job done

A = pd.DataFrame({"X1": [0], "Y1": [0], "X2": [0], "Y2": [0], "X3": [0], "Y3": [0], "X4": [0], "Y4": [0]})
B = pd.DataFrame({"X1": [9], "Y1": [99.9]})

B = B.loc[:, (B > 0).any(axis=0)]
cols = B.columns.tolist()
C = A
C[cols] = B[cols]

answered Dec 2, 2020 at 23:04

fthomson

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2 Comments

Cainã Max Couto da Silva Over a year ago

Here, you're also changing the values of A by reference. I'd create C as a copy of A.

fthomson Over a year ago

Good point agreed, I prefer your solution anyways :)

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