[FIXED] How to merge all csv files into one file and have the data stacked under the original headers?

Issue

Im new to python and trying to understand data manipulation.

I have a folder with several files. Some of which are csv's. I want to merge all of the csvs - approximately 400 of them into one single csv and all the data to be stacked

for example if the first csv has a dataframe-

transcript  confidence  from    to  speaker Negative Neutral    Positive    compound
thank you   0.85    1.39    1.65    0   0   0.754              0.246         0.7351

second has a dataframe:

 transcript confidence  from    to  speaker Negative Neutral    Positive compound
    welcome     0.95       1.39   1.65  0   0       0.754        0.201   0.8351

I want the final df to look like -

transcript  confidence from to  speaker Negative Neutral      Positive       compound
thank you   0.85      1.39  1.65    0   0       0.754              0.246         0.7351
welcome     0.95      1.39  1.65    0   0       0.754              0.201         0.8351

I tried-

import glob
import pandas as pd

# Folder containing the .csv files to merge
file_path = "C:\\Users\\Desktop"

# This pattern \\* selects all files in a directory
pattern = file_path + "\\*"
files = glob.glob(pattern)

# Import first file to initiate the dataframe
df = pd.read_csv(files[0],encoding = "utf-8", delimiter = ",")

# Append all the files as dataframes to the first one
for file in files[1:len(file_list)]:
    df_csv = pd.read_csv(file,encoding = "utf-8", delimiter = ",")
    df = df.append(df_csv)

But it did not work. How can I solve this issue?

Solution

This should help:

import pandas as pd
import glob
import os.path

file_path = "C:/Users/Desktop"

data = []
for csvfile in glob.glob(os.path.join(file_path, "*.csv")):
    df = pd.read_csv(csvfile, encoding="utf-8", delimiter=",")
    data.append(df)

data = pd.concat(data, ignore_index=True)

Answered By - Corralien