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# Python Pandas count most frequent occurrences

By : 3-Ply
Date : October 24 2020, 08:10 PM
Does that help @ScottBoston's answer shows vectorized (hence probably faster) ways to achieve this.
Top occurring
code :
``````from collections import Counter
from itertools import chain

n = 3
individual_components = chain.from_iterable(df['components'].str.split(', '))
counter = Counter(individual_components)
print(counter.most_common(n))
# [('e05', 6), ('e04', 5), ('a02', 4)]
``````
``````from collections import Counter
from itertools import combinations

n = 3
individual_components = []
for components in df['components']:
order_components = sorted(components.split(', '))
individual_components.extend(combinations(order_components, n))
counter = Counter(individual_components)
print(counter.most_common(n))
# [(('e04', 'e05', 'с43'), 4), (('a02', 'b08', 'e05'), 3), (('a02', 'd07', 'e05'), 3)]
``````

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## VBA: Count number of occurrences of the most frequent character in a string

By : Ange Zigre
Date : March 29 2020, 07:55 AM
To fix the issue you can do Not sure why you got a down vote, but here is one way to get the count of the most frequent character in a string.
code :
``````Sub chCount()
Dim str As String: str = "abldfeoslgsasasessasae"

Dim Ruler As Variant
Dim Counter As Long
Dim lCount As Long
Dim maxCount As Long

lCount = Len(str)

For ch = 1 To lCount
Ruler = Split(str, Mid(str, ch, 1))
Counter = UBound(Ruler)
If maxCount < Counter Then
maxCount = Counter
End If
Next ch

msgbox(maxCount)

End Sub
``````

## count of unique occurrences of a value pandas python

By : Umar Chaudhary
Date : March 29 2020, 07:55 AM
wish helps you So I have an extremely simple dataframe: , Just use map to map your column onto its value_counts:
code :
``````>>> x
A
0  1
1  1
2  1
3  2
4  2
>>> x['unique'] = x.A.map(x.A.value_counts())
>>> x
A  unique
0  1       3
1  1       3
2  1       3
3  2       2
4  2       2
``````

## python count occurrences in csv with pandas

By : Piyush Bondre
Date : March 29 2020, 07:55 AM
will be helpful for those in need I'm new to Python and I'm trying to work on a small project and got a little confused. , I'd do it this way:
code :
``````In [220]: d1.stack().value_counts().to_frame('car').loc[d2.super_car_name]
Out[220]:
car
Ferrari     2
BMW         2
Mercedes    1
``````
``````In [218]: d1
Out[218]:
first_Car  second_car
0       Mazda       Skoda
1     Ferrari  Volkswagen
2  Volkswagen      Toyota
3         BMW     Ferrari
4         BMW    Mercedes

In [219]: d2
Out[219]:
super_car_name
0        Ferrari
1            BMW
2       Mercedes
``````

## How to count occurrences of specified value in column in Pandas using Python

By : ManUnited JDZ
Date : March 29 2020, 07:55 AM
seems to work fine I have the following dataframe where I need to count how many rows contain 'False' in column IsCleared. , You have a boolean mask. So why not work with it?
code :
``````>>> (~df.IsCleared).sum()
3
``````

## Count the most frequent values in a row pandas and make a column with that most frequent value

By : TheFrank242
Date : March 29 2020, 07:55 AM
it should still fix some issue Use DataFrame.mode with select first column by positions with DataFrame.iloc:
code :
``````df['result'] = df.mode(axis=1).iloc[:, 0]
print (df)
a  b  c  result
0  3  3  3       3
1  3  3  3       3
2  3  3  3       3
3  3  3  3       3
4  2  3  2       2
5  3  3  3       3
6  1  2  1       1
7  2  3  2       2
8  0  0  0       0
9  0  1  0       0
``````