Concatenate multiple file rowwise in a single dataframe with the same header name - dataframe

Question

I have 400 csv files and all the files contains single column which has 4667 rows . Every row has name and corresponding value for example "A=54,B=56 and so on till 4667 rows. My problem statement is :
1. fetch the variable name and put it different columns
2. fetch the corresponding variable value and put it in the next rows above the columns.
3. Now, Do this step for all the 400 files and append all the corresponding values in the above rows which makes 400 rows.
I have done for the single file and how to do with the multiple files . I don't Know
import glob
from collections import OrderedDict
path =r'Github/dataset/Raw_Dataset/'
filenames = glob.glob(path + "/*.csv")
dict_of_df = OrderedDict((f, pd.read_csv((f),header=None,names=['Devices'])) for f in filenames)
eda=pd.concat(dict_of_df)
I

Answer 1

Do you mean a concatenation?
you could use pandas like this:
import pandas as pd
df1 = pd.DataFrame(columns=["A","B","C","D"],data=[["1","2","3","4"]])
df2 = pd.DataFrame(columns=["A","B","C","D"],data=[["5","6","7","8"]])
df3 = pd.DataFrame(columns=["A","B","C","D"],data=[["9","10","11","12"]])
df_concat = pd.concat([df1, df2, df3])
print(df_concat)
In combination with a loop through the files in the folder ending with ".csv" it would be:
import os
import pandas as pd
path = r"C:\YOUR\DICTIONARY"
df_concat = pd.DataFrame()
for filename in os.listdir(path):
if filename.endswith(".csv"):
print(filename)
df_temp = pd.read_csv(path + "\\" + filename)
df_concat = pd.concat([df_concat, df_temp])
continue
else:
continue