len(gapminder['country'].unique().tolist())
set(df['region'].values.tolist())
# Create a list of unique values by turning the # pandas column into a set list(set(df.trucks))
# Create a list of unique values in df.trucks list(df['trucks'].unique())
# 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()
# 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)
References
https://pythonprogramming.net/graph-visualization-python3-pandas-data-analysis/
https://www.geeksforgeeks.org/get-unique-values-from-a-column-in-pandas-dataframe/
https://chrisalbon.com/python/data_wrangling/pandas_find_unique_values/
https://cmdlinetips.com/2018/01/how-to-get-unique-values-from-a-column-in-pandas-data-frame/