i am using below formula to get value count froma. column in a dataframe:
new_data = df['item'].value_counts()
which give me below result
Apples 3
Green bananas 2
Bananas 1
Oranges 1
what i want is to get output for every item count in in new column like the below excel example
Any help or guidance is appreciated. Thank you
Use Series.map for your solution:
new_data = df['item'].value_counts()
df['Occurence'] = df['item'].map(new_data)
One row solution:
df['Occurence'] = df['item'].map(df['item'].value_counts())
If there is multiple columns:
cols = ['item','item1']
for c in cols:
df[f'Occurence_{c}'] = df[c].map(df[c].value_counts())
df.loc[len(df), cols] = df[cols].sum()
Or:
df = df.join(df[cols].apply(lambda x: x.map(x.value_counts())).add_prefix('Occurence_'))
df['Occurence1'] = df['item1'].map(df['item1'].value_counts()) ?Try with transform
df['new'] = df.groupby('item')['item'].transform('count')
Or by the index:
df.set_index('item').assign(count=df['item'].value_counts()).reset_index()
Since column assigning corresponds to the index, this way would do it.
