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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