Let’s discuss how to get unique values from a column in Pandas DataFrame.
Create a simple dataframe with dictionary of lists, say columns name are A, B, C, D, E with duplicate elements.
Now, let’s get the unique values of a column in this dataframe.
Example #1: Get the unique values of ‘B’ column
# Import pandas package import pandas as pd # create a dictionary with five fields each data = { 'A' :[ 'A1' , 'A2' , 'A3' , 'A4' , 'A5' ], 'B' :[ 'B1' , 'B2' , 'B3' , 'B4' , 'B4' ], 'C' :[ 'C1' , 'C2' , 'C3' , 'C3' , 'C3' ], 'D' :[ 'D1' , 'D2' , 'D2' , 'D2' , 'D2' ], 'E' :[ 'E1' , 'E1' , 'E1' , 'E1' , 'E1' ] } # Convert the dictionary into DataFrame df = pd.DataFrame(data) # Get the unique values of 'B' column df.B.unique() |
Output:
Example #2: Get the unique values of ‘E’ column
# Import pandas package import pandas as pd # create a dictionary with five fields each data = { 'A' :[ 'A1' , 'A2' , 'A3' , 'A4' , 'A5' ], 'B' :[ 'B1' , 'B2' , 'B3' , 'B4' , 'B4' ], 'C' :[ 'C1' , 'C2' , 'C3' , 'C3' , 'C3' ], 'D' :[ 'D1' , 'D2' , 'D2' , 'D2' , 'D2' ], 'E' :[ 'E1' , 'E1' , 'E1' , 'E1' , 'E1' ] } # Convert the dictionary into DataFrame df = pd.DataFrame(data) # Get the unique values of 'E' column df.E.unique() |
Output:
Example #3: Get number of unique values in a column
# Import pandas package import pandas as pd # create a dictionary with five fields each data = { 'A' :[ 'A1' , 'A2' , 'A3' , 'A4' , 'A5' ], 'B' :[ 'B1' , 'B2' , 'B3' , 'B4' , 'B4' ], 'C' :[ 'C1' , 'C2' , 'C3' , 'C3' , 'C3' ], 'D' :[ 'D1' , 'D2' , 'D2' , 'D2' , 'D2' ], 'E' :[ 'E1' , 'E1' , 'E1' , 'E1' , 'E1' ] } # Convert the dictionary into DataFrame df = pd.DataFrame(data) # Get number of unique values in column 'C' df.C.nunique(dropna = True ) |
Output: