Get the specified row value of a given Pandas DataFrame

Last Updated : 17 Aug, 2020

Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns).

Now let's see how to get the specified row value of a given DataFrame.

We shall be using loc[ ], iloc[ ], and [ ] for a data frame object to select rows and columns from our data frame.

iloc[ ] is used to select rows/ columns by their corresponding labels.
loc[ ] is used to select rows/columns by their indices.
[ ] is used to select columns by their respective names.

Method 1: Using iloc[ ].

Example: Suppose you have a pandas dataframe and you want to select a specific row given its index.

Python3

# import pandas library
import pandas as pd

# Creating a dictionary
d = {'sample_col1': [1, 2, 3],
     'sample_col2': [4, 5, 6], 
     'sample_col3': [7, 8, 9]} 

# Creating a Dataframe
df = pd.DataFrame(d) 

# show the dataframe 
print(df) 

print()

# Select Row No. 2
print(df.iloc[2])

Output:

Method 2: Using loc[ ].

Example: Suppose you want to select rows where the value of a given column is given.

Python3

# import pandas library
import pandas as pd

# Creating a dictionary
d = {'sample_col1': [1, 2, 1],
     'sample_col2': [4, 5, 6], 
     'sample_col3': [7, 8, 9]} 

# Creating a Dataframe
df = pd.DataFrame(d) 

# show the dataframe
print(df) 

print()

# Select rows where sample_col1 is 1
print(df.loc[df['sample_col1'] == 1])

Output:

Method 3: Using [ ] and iloc[ ].

Example: Suppose you want only the values pertaining to specific columns of a specific row.

Python3

# import pandas library
import pandas as pd

# Creating a dictionary
d = {'sample_col1': [1, 2, 1],
     'sample_col2': [4, 5, 6], 
     'sample_col3': [7, 8, 9]}  

# Creating a Dataframe
df = pd.DataFrame(d) 

# show the dataframe
print(df) 

print()

# Display column 1 and 3 for row 2
print(df[['sample_col1' , 'sample_col3']].iloc[1])