How to combine multiple CSV files into one DataFrame

If your all .csv files in the same directory, you can use the following methods:

df = pd.concat(map(pd.read_csv, all_files))

Full Source:

import pandas as pd import numpy as np import glob import os path = r'D:\csv' all_files = glob.glob(path + "/*.csv") df = pd.concat(map(pd.read_csv, all_files))

Method 2: Reading Multiple CSVs Into Pandas


Reading Multiple CSVs Into Pandas
import pandas as pd import numpy as np import glob path = r'D:\csv' all_files = glob.glob(path + "/*.csv") df_files = (pd.read_csv(f) for f in all_files) df = pd.concat(df_files, ignore_index=True)
Glob: The python module glob provides Unix style pathname pattern expansion. So, using glob.glob('*.csv') will give you all the .csv files in a folder as a list.




Related Topics
  1. Pandas DataFrame: GroupBy Examples
  2. Pandas DataFrame Aggregation and Grouping
  3. How to Sort Pandas DataFrame
  4. Pandas DataFrame: query() function
  5. Finding and removing duplicate rows in Pandas DataFrame
  6. How to Replace NaN Values With Zeros in Pandas DataFrame
  7. How to read CSV File using Pandas DataFrame.read_csv()
  8. How to Convert Pandas DataFrame to NumPy Array
  9. How to shuffle a DataFrame rows
  10. Create new column in DataFrame based on the existing columns
  11. New Pandas dataframe column based on if-else condition
  12. How to Convert a Dictionary to Pandas DataFrame
  13. Rename Pandas columns/index names (labels)