Skip to content
Related Articles
Open in App
Not now

Related Articles

Creating a dataframe using CSV files

Improve Article
Save Article
  • Difficulty Level : Medium
  • Last Updated : 17 Feb, 2022
Improve Article
Save Article

CSV files are the “comma-separated values”, these values are separated by commas, this file can be viewed like an 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. Creating a pandas data frame using CSV files can be achieved in multiple ways.
Note: Get the csv file used in the below examples from here.
Method #1: Using read_csv() method: read_csv() is an important pandas function to read csv files and do operations on it.
Example
 

Python3




# Python program to illustrate
# creating a data frame using CSV files
 
# import pandas module
import pandas as pd
 
# creating a data frame
df = pd.read_csv("CardioGoodFitness.csv")
print(df.head())

Output:
 

csv-to-df-pandas

Method #2: Using read_table() method: read_table() is another important pandas function to read csv files and create data frame from it.
Example
 

Python3




# Python program to illustrate
# creating a data frame using CSV files
 
# import pandas module
import pandas as pd
 
# creating a data frame
df = pd.read_table("CardioGoodFitness.csv", delimiter =", ")
print(df.head())

Output:
 

csv-to-df-pandas

Method #3: Using the csv module: One can directly import the csv files using the csv module and then create a data frame using that csv file.
Example
 

Python3




# Python program to illustrate
# creating a data frame using CSV files
 
# import pandas module
import pandas as pd
# import csv module
import csv
 
with open("CardioGoodFitness.csv") as csv_file:
    # read the csv file
    csv_reader = csv.reader(csv_file)
 
    # now we can use this csv files into the pandas
    df = pd.DataFrame([csv_reader], index = None)
 
# iterating values of first column
for val in list(df[1]):
    print(val)

Output
 

['TM195', '18', 'Male', '14', 'Single', '3', '4', '29562', '112']

 


My Personal Notes arrow_drop_up
Related Articles

Start Your Coding Journey Now!