Reading CSV files
If our data files are in CSV format then the read_csv() method must be used. read_csv takes a file path as an argument. it reads the content of the CSV. To read multiple CSV files we can just use a simple for loop and iterate over all the files.
Example: Reading Multiple CSV files using Pandas
In this example we make a list of our data files or file path and then iterate through the file paths using a for loop, a for loop is used to iterate through iterables like list, tuples, strings, etc. And then create a data frame using pd.DataFrame(), concatenate each dataframe into a main dataframe using pd.concat(), then convert the final main dataframe into a CSV file using to_csv() method which takes the name of the new CSV file we want to create as an argument.
Python3
# importing pandas import pandas as pd file_list=['a.csv','b.csv','c.csv'] main_dataframe = pd.DataFrame(pd.read_csv(file_list[0])) for i in range(1,len(file_list)): data = pd.read_csv(file_list[i]) df = pd.DataFrame(data) main_dataframe = pd.concat([main_dataframe,df],axis=1) print(main_dataframe) |
Output:
How to read multiple data files into Pandas?
In this article, we are going to see how to read multiple data files into pandas, data files are of multiple types, here are a few ways to read multiple files by using the pandas package in python.
The demonstrative files can be download from here