How to concat dataframes iteratively from different folders using python

Question

So I'm trying to concat (one after the other) dataframes from several different folders and put it on a single csv file, keeping just the first heading and erasing the following ones. What I want to do is make the code run through every folder in a specific directory, get the right csv file from there and add the data to a final csv folder. Here's what I've tried so far:

for runs in range(len(runlist)) :
if fnmatch.fnmatch(runlist[runs], '*month*') :
  data_run=glob.glob((runlist[runs]+'/processing/*day*.csv')) ##setting the directory
  for file in data_run:
    final_df = pd.concat([pd.read_csv(file, header=None) for file in data_run], ignore_index=True, axis=0)
    final_df.to_csv('date_all.csv', index=False)
    date_all=pd.read_csv("date_all.csv")
    date_all_col=date_all["7"]
    date_all_col=pd.to_numeric(date_all_col, errors='coerce')
    date_all_col.plot.hist()

The results I'm getting are like this:

0              WA()
1              23.12
2              12.15
3              13.52
Name: 7, dtype: object
0              WA()
1              35.18
2              14.85
3              26.16
Name: 7, dtype: object
0              WA()
1              62.12
2              45.52
3              18.22

And so on and when I plot a histogram: https://i.stack.imgur.com/lZpFa.png

It's just not right, I want the WA columns to be plot all together

Answer 1

for runs in range(len(runlist)):
    if fnmatch.fnmatch(runlist[runs], '*month*'):
        data_run = glob.glob((runlist[runs]+'/processing/*day*.csv')) ##setting the directory
    final_df = pd.Dataframe()
    for file in data_run:
        added_df = pd.read_csv(file)['WA()']
        added_df = pd.to_numeric(added_df, errors='coerce')
        added_df.plot.hist()
        final_df = pd.concat([final_df, added_df], axis=1)
    final_df.to_csv('date_all.csv', index=False)