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.

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Python | Pandas DataFrame.loc[]