how to get distinct value in a column dataframe in python
df.column.unique()
how to get distinct value in a column dataframe in python
df.column.unique()
dataframe unique values in each column
for col in df:
print(df[col].unique())
unique values in dataframe column count
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
pandas distinct
>gapminder['continent'].unique()
array(['Asia', 'Europe', 'Africa', 'Americas', 'Oceania'], dtype=object)
unique entries in column pandas
# 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()
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