Skip to content
Related Articles

Related Articles

Improve Article

Python | Pandas DataFrame.loc[]

  • Difficulty Level : Basic
  • Last Updated : 20 Feb, 2019

Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas.

Pandas DataFrame.loc attribute access a group of rows and columns by label(s) or a boolean array in the given DataFrame.

Syntax: DataFrame.loc

Parameter : None

Returns : Scalar, Series, DataFrame



Example #1: Use DataFrame.loc attribute to access a particular cell in the given Dataframe using the index and column labels.




# importing pandas as pd
import pandas as pd
  
# Creating the DataFrame
df = pd.DataFrame({'Weight':[45, 88, 56, 15, 71],
                   'Name':['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'],
                   'Age':[14, 25, 55, 8, 21]})
  
# Create the index
index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5']
  
# Set the index
df.index = index_
  
# Print the DataFrame
print(df)

Output :

Now we will use DataFrame.loc attribute to return the value present in the ‘Name’ column corresponding to the ‘Row_2’ label.




# return the value
result = df.loc['Row_2', 'Name']
  
# Print the result
print(result)

Output :

As we can see in the output, the DataFrame.loc attribute has successfully returned the value present at the desired location in the given DataFrame.
 
Example #2: Use DataFrame.loc attribute to return two of the column in the given Dataframe.




# importing pandas as pd
import pandas as pd
  
# Creating the DataFrame
df = pd.DataFrame({"A":[12, 4, 5, None, 1], 
                   "B":[7, 2, 54, 3, None], 
                   "C":[20, 16, 11, 3, 8], 
                   "D":[14, 3, None, 2, 6]}) 
  
# Create the index
index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5']
  
# Set the index
df.index = index_
  
# Print the DataFrame
print(df)

Output :

Now we will use DataFrame.loc attribute to return the values present in the ‘A’ and ‘D’ column of the Dataframe.




# return the values.
result = df.loc[:, ['A', 'D']]
  
# Print the result
print(result)

Output :

As we can see in the output, the DataFrame.loc attribute has successfully returned the desired columns of the dataframe.

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course




My Personal Notes arrow_drop_up
Recommended Articles
Page :