How to skip errors when merging dataframe

I’m trying to merge dataframes but it raised errors and I don’t know how to solve. Below is my sample code:

import pandas as pd

df1 = pd.read_csv('https://raw.githubusercontent.com/hoatranobita/Jobs/main/UMAPdf%20(3).csv')

counts_url = "https://www.dropbox.com/s/pivx6ktd4zfj4jn/counts.csv?dl=1"
df2 = pd.read_table(counts_url,sep=',', header=(0))
df3 = df2.T

df4 = pd.read_table("https://raw.githubusercontent.com/hoatranobita/Jobs/main/annotated_clusters.csv", sep=',', index_col=1)
df4 = df4.rename(columns={"cluster": "clusters"}, errors="raise")
df4.clusters = df4.clusters.astype('str'

selected_gene = df4.index
sel_len = len(selected_gene)
#sel_len = int(sel_len)

for i in range(sel_len):
    df1[selected_gene[i]] = df3[selected_gene[i]].values
df1

With this code it raised errors as below:

if is_scalar(key) and isna(key) and not self.hasnans:

KeyError: 'SERPINB13'

I understand that have some mismatch data between dataframes but I don’t know how to skip errors. I mean that how can I skip KeyError from loop.

Below is my desire Ouput:

UMAP1   UMAP2   UMAP3   Id  clusters    AKR1C1  PERP    BIRC5   MS4A6A  CTSL    TRBC2   JCHAIN  SCEL    PLK1    SCGB3A1 DCN LPL VWF RGS5
0   8.114442    4.716549    9.492684    X24_CTGACACAATGC    0   0   2   0   0   0   0   0   0   0   0   0   0   0   0
1   9.849996    5.723419    9.249526    X24_CTGGTTAGAGTA    0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
2   5.677463    1.173194    5.189664    X24_AGAGCATATACA    3   0   0   0   0   0   0   0   0   0   0   0   0   0   0
3   8.003273    4.559005    9.536844    X24_ATTTCTGGTGCT    0   0   2   0   0   0   0   0   3   0   0   0   0   0   0
4   9.555323    5.731429    9.267872    X24_AATCTGACAGCT    0   0   3   0   0   0   0   0   0   0   0   0   0   0   0

Thank you.

>Solution :

You could use something like this:

try:
    "code"
except IndexError: # IndexError as an example
    pass