pandas unique values in column

#List unique values in the df['name'] column
df.name.unique()

df.groupby('mID').agg(['count', 'size', 'nunique']).stack()


             dID  hID  uID
mID                       
A   count      5    5    5
    size       5    5    5
    nunique    3    5    5
B   count      2    2    2
    size       2    2    2
    nunique    2    2    2
C   count      1    1    1
    size       1    1    1
    nunique    1    1    1

for col in df:
    print(df[col].unique())

df['Column_name'].value_counts()

df['hID'].nunique()
5

df.nunique()

# Import modules
import pandas as pd

# Set ipython's max row display
pd.set_option('display.max_row', 1000)

# Set iPython's max column width to 50
pd.set_option('display.max_columns', 50)
# Create an example dataframe
data = {'name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'], 
        'year': [2012, 2012, 2013, 2014, 2014], 
        'reports': [4, 24, 31, 2, 3]}
df = pd.DataFrame(data, index = ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'])
df

#List unique values in the df['name'] column
df.name.unique()

# get the unique values (rows)
df.drop_duplicates()

df.groupby('param')['column'].nunique().sort_values(ascending=False).unique().tolist()