Convert CSV to pandas DataFrame

In this pandas tutorial, we will discuss how to convert csv to pandas DataFrame.

 

Introduction

CSV stands for comma separated value. 

DataFrame in pandas is an two dimensional data structure that will store data in two dimensional format. One dimension refers to a row and second dimension refers to a column, So It will store the data in rows and columns.

 

We will convert CSV to pandas dataframe by using read_csv() method.So we will consider the below csv file for all the examples.

We observed that this file has 4 rows and 4 columns, column names - [college_id,college_name,college_address,Total Staff] and row names are - ['one','two','three','four'].

 

Example 1: Convert csv to pandas dataframe with no parameters.

In this example, we will convert csv to dataframe without any parameters.

Syntax:

pandas.read_csv("csv_file.csv")

where, csv_file.csv is the file name of csv.

import pandas as pd

#create dataframe from the csv file
data= pd.read_csv("mycsv.csv")


#display the dataframe
print(data)

Output:

  college_id       college_name college_address  Total Staff
0      c-001  vignan university          guntur         1200
1      c-021               vvit          guntur         3422
2      c-002           RVR - JC          guntur         5644
3      c-004  Andhra University          guntur          670

Example 2: Convert csv to pandas dataframe by setting custom index.

In this example, we will convert csv to dataframe by setting the custon index(from cvs file).Sp this column will act as index for thr dataframe. The parameter that is used to set the custom index is 'index_col'.

Syntax:

pandas.read_csv("csv_file.csv",index_col=column_name)

where, csv_file.csv is the file name of csv and column_name is the column label in csv which will be the index in pandas dataframe.

Here we will set the college_id column as custom index.

import pandas as pd

#create dataframe from the csv file
data= pd.read_csv("mycsv.csv",index_col='college_id')


#display the dataframe
print(data)

Output:

                 college_name college_address  Total Staff
college_id                                                
c-001       vignan university          guntur         1200
c-021                    vvit          guntur         3422
c-002                RVR - JC          guntur         5644
c-004       Andhra University          guntur          670

Example 3: Convert csv to pandas dataframe by setting column labels.

In this example, we will convert csv to dataframe by setting the column labels using names parameter through list.

Syntax:

pandas.read_csv("csv_file.csv",names=[column_names])

where, csv_file.csv is the file name of csv and set column labels as - ['col1','col2','col3','col4']

import pandas as pd

#create dataframe from the csv file
data= pd.read_csv("mycsv.csv",names=['col1','col2','col3','col4'])


#display the dataframe
print(data)

Output:

         col1               col2             col3         col4
0  college_id       college_name  college_address  Total Staff
1       c-001  vignan university           guntur         1200
2       c-021               vvit           guntur         3422
3       c-002           RVR - JC           guntur         5644
4       c-004  Andhra University           guntur          670

Example 4: Convert csv to pandas dataframe by setting top rows.

In this example, we will convert csv to dataframe by setting only top n rows through nrows paramater. It will take an integer value and display rows from the top.

Syntax:

pandas.read_csv("csv_file.csv",nrows=n)

where, csv_file.csv is the file name of csv and display the top 3 rows.

import pandas as pd

#create dataframe from the csv file
data= pd.read_csv("mycsv.csv",nrows=3)


#display the dataframe
print(data)

Output:

  college_id       college_name college_address  Total Staff
0      c-001  vignan university          guntur         1200
1      c-021               vvit          guntur         3422
2      c-002           RVR - JC          guntur         5644