ValueError: object too deep for desired array while using cross correlation

Question

I am trying to investigate the cross correlation of two DataFrames. The code is given here:

df1 = pd.DataFrame({"A":[1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1]})
df2 = pd.DataFrame({"A":[7191, 7275, 9889, 9934, 9633, 9924, 9650, 9341, 8820, 8784, 8869]})

np.correlate(df1, df2)

But I get this error:

https://i.sstatic.net/XedfI.jpg

Any ideas?

Answer 1

You're getting this error as you're passing as a dataframe, which is 2D. np.correlate is for cross-correlation of two 1-dimensional sequences. So try.

np.correlate(df1.squeeze(), df2.squeeze())

which outputs array([80556], dtype=int64).

---

Edit

Based on your suggestion, try

# You will need to change your column names, like 
df1 = pd.DataFrame({"A":[1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1]})
df2 = pd.DataFrame({"B":[7191, 7275, 9889, 9934, 9633, 9924, 9650, 9341, 8820, 8784, 8869]})

df1.join(df2).corr()

which outputs

            A           B
A   1.000000    -0.174287
B   -0.174287   1.000000

As suggested by piRSquared in the comments, you can also use df1.corrwith(df2) to return a single value.