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Different ways to import csv file in Pandas

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  • Difficulty Level : Basic
  • Last Updated : 19 Dec, 2018

CSV files are the “comma separated values”, these values are separated by commas, this file can be view like as excel file. In Python, Pandas is the most important library coming to data science. We need to deal with huge datasets while analyzing the data, which usually can get in CSV file format.

Let’s see the different ways to import csv file in Pandas.

Method #1: Using read_csv() method.




# importing pandas module  
import pandas as pd  
      
# making data frame  
    
df.head(10

Output:

 
Providing file_path.




# import pandas as pd
import pandas as pd
   
# Takes the file's folder
filepath = r"C:\Gfg\datasets\nba.csv"
   
# read the CSV file
df = pd.read_csv(filepath)
   
# print the first five rows
print(df.head())

Output:

 
Method #2: Using csv module.

One can directly import the csv files using csv module.




# import the module csv
import csv
import pandas as pd
   
# open the csv file
with open(r"C:\Users\Admin\Downloads\nba.csv") as csv_file: 
      
    # read the csv file
    csv_reader = csv.reader(csv_file, delimiter=',')
       
    # now we can use this csv files into the pandas
    df = pd.DataFrame([csv_reader], index=None)
    df.head()
      
# iterating values of first column
for val in list(df[1]):
    print(val)

Output:


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