I have a pandas df like this.

         up_value        valsup
0     59044.21272   59044.21272
1     59040.68568   59158.53136
2     59044.21272   59279.91816
3     59040.69570   59394.23280
4     59044.22274   59515.63370
...           ...           ...
6081  58917.07896  774036.35472
6082  58917.07896  774153.95368
6083  58917.08898  774271.68432
6084  58917.07896  774389.15160
6085  58917.08898  774506.88228

                 

I'm trying to use numpy argwhere and create a new pandas column like this.

df["idx_up"] = np.argwhere(df["valsup"].values > df["up_value"].values)

But it returns the following error.

ValueError: Length of values (6085) does not match length of index (6086)

When I do, print(np.argwhere(df["valsup"].values > df["up_value"].values)), the output looks like this.

[[   1]
 [   2]
 [   3]
 ...
 [6083]
 [6084]
 [6085]]

So it seems like np.argwhere only returns 6085 values instead of 6086.

I wanna assign the output to pandas. Can someone tell me how to fix the error?

Thanks

CodePudding user response：

At the code from one of the answers at that url,

idx_up = idx_up[0][0] if len(idx_up) else -1

this code checks only idx_up at index 0.

You should add column first like

df['idx_up'] = -1

and update like

df['idx_up'].iloc[[x[0] for x in idx_up]] = [x[0] for x in idx_up]