PYTHON

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

python count number of unique elements in a list

# Basic syntax:
len(set(my_list))
# By definition, sets only contain unique elements, so when the list
# is converted to a set all duplicates are removed. 

# Example usage:
my_list = ['so', 'so', 'so', 'many', 'duplicated', 'words']
len(set(my_list))
--> 4

# Note, list(set(my_list)) is a useful way to return a list containing
#	only the unique elements in my_list

Count unique values Pandas

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

count unique values pandas

df['hID'].nunique()
5

count unique elements in list python

from collections import Counter

words = ['a', 'b', 'c', 'a']

Counter(words).keys() # equals to list(set(words))
Counter(words).values() # counts the elements' frequency

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

counting unique values python

df.loc[df['mID']=='A','hID'].agg(['nunique','count','size'])

python count unique values in list

len(set(["word1", "word1", "word2", "word3"]))
# set is like a list but it removes duplicates
# len counts the number of things inside the set