Python | Pandas DataFrame.loc[]
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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