Q:

Import multiple csv files into pandas and concatenate into one DataFrame

I would like to read several csv files from a directory into pandas and concatenate them into one big DataFrame. I have not been able to figure it out though. Here is what I have so far:
import glob
import pandas as pd

# get data file names
path =r'C:\DRO\DCL_rawdata_files'
filenames = glob.glob(path + "/*.csv")

dfs = []
for filename in filenames:
    dfs.append(pd.read_csv(filename))

# Concatenate all data into one DataFrame
big_frame = pd.concat(dfs, ignore_index=True)

I guess I need some help within the for loop???

A:

If you have same columns in all your csv files then you can try the code below.
I have added header=0 so that after reading csv first row can be assigned as the column names.
import pandas as pd
import glob

path = r'C:\DRO\DCL_rawdata_files' # use your path
all_files = glob.glob(path + "/*.csv")

li = []

for filename in all_files:
    df = pd.read_csv(filename, index_col=None, header=0)
    li.append(df)

frame = pd.concat(li, axis=0, ignore_index=True)

A:

An alternative to darindaCoder's answer:
path = r'C:\DRO\DCL_rawdata_files'                     # use your path
all_files = glob.glob(os.path.join(path, "*.csv"))     # advisable to use os.path.join as this makes concatenation OS independent

df_from_each_file = (pd.read_csv(f) for f in all_files)
concatenated_df   = pd.concat(df_from_each_file, ignore_index=True)
# doesn't create a list, nor does it append to one

A:

import glob, os    
df = pd.concat(map(pd.read_csv, glob.glob(os.path.join('', "my_files*.csv"))))

