PYTHON

return count of unique values pandas

#TO count repetition of each unique values(to find How many times the same-
# unique value is appearing in the data)

item_counts = df["Your_Column"].value_counts()
#Returns Dictionary => {"Value_name" : number_of_appearences} 

count unique pandas

df['column'].nunique()

dataframe unique values in each column

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

count unique values in pandas column

df['column_name'].value_counts()

values of unique from dataframe with count

data = df.groupby('ColumnName')['IDColumnName'].nunique()
print(data)

how to count number of unique values in a column python

pd.value_counts(df.Account_Type)

Gold        3
Platinum    1
Name: Account_Type, dtype: int64

get count of unique values in column pandas

df = df.groupby('domain')['ID'].nunique()

print (df)
domain
'facebook.com'    1
'google.com'      1
'twitter.com'     2
'vk.com'          3
Name: ID, dtype: int64

how to count unique values in a column dataframe in python

dataframe.column.nunique()

Count unique values Pandas

df = df.groupby('domain')['ID'].nunique()

how to count unique values in dataframe df python

#count unique values in each column
df.nunique()

#count unique values in each row
df.nunique(axis=1)

count unique values pandas

df['hID'].nunique()
5

How to Find Unique Values in a Column in Pandas

# import pandas library
import pandas as pd

# create pandas DataFrame
df = pd.DataFrame({'fruits': ['orange', 'mango', 'apple', 'grapes', 'orange', 'mango'],
                   'price': ['40', '80', '30', '40', '30', '80'],
                   'quantity': ['200', '300', '300', '400', '200', '800']
                   })

# get the unique value of column fruits
print(df.fruits.unique())

count unique pandas

df.nunique()

how to get unique value of all columns in pandas

print(df.apply(lambda col: col.unique()))

python - count how many unique in a column

df['var_1'].nunique()   # How many unque values are present in a variable

Find and count unique values of a single column in Pandas DataFrame

# import pandas library
import pandas as pd

# create pandas DataFrame
df = pd.DataFrame({'fruits': ['orange', 'mango', 'apple', 'grapes', 'orange', 'mango'],
                   'price': ['40', '80', '30', '40', '30', '80'],
                   'quantity': ['200', '300', '300', '400', '200', '800']
                   })

# get the count unique values of column fruits
print(df.fruits.value_counts())

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

dataframe python unique values rows

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

Find unique values in all columns in Pandas DataFrame

# import pandas library
import pandas as pd

# create pandas DataFrame
df = pd.DataFrame({'fruits': ['orange', 'mango', 'apple', 'grapes', 'orange', 'mango'],
                   'price': ['40', '80', '30', '40', '30', '80'],
                   'quantity': ['200', '300', '300', '400', '200', '800']
                   })

# get the unique value of all columns
for col in df:
  print(df			
							
		.unique())

unique rows in dataframe

In [33]: df[df.columns[df.apply(lambda s: len(s.unique()) > 1)]]
Out[33]: 
   A  B
0  0  a
1  1  b
2  2  c
3  3  d
4  4  e

dataframe number of unique rows

1
# get the unique values (rows) by retaining last row
2
df.drop_duplicates(keep='last')

count unique values in python

words = ['a', 'b', 'c', 'a']
unique_words = set(words)             # == set(['a', 'b', 'c'])
unique_word_count = len(unique_words) # == 3

pandas count distinct values in column

#column name ISSDTM
pd.to_datetime(df.ISSDTM, errors='coerce').dt.year

#result
0    2013
1    2013
2    2009
3    2009
Name: ISSDTM, dtype: int64 

pandas get number unique values in column

df["Your_Column"].nunique()