CODEWITHSUNDEEP
pythonpandas
Bardiya Choupani
Bardiya Choupani

Reputation: 165

Count occurrences in Pandas data frame

I have the following data frame:

enter image description here

I'm looking to come up with this data frame: enter image description here

which is counting the occurrences of pipe delimited strings in position and type column.

Upvotes: 0

Views: 632

Answers (2)

plasmon360
plasmon360

Reputation: 4199

you could split each value and then apply count method. see example below

df  = pd.DataFrame.from_dict({'POSITION':['FRONT|FRONT|BACK|BACK|BACK'], 'TYPE': ['EXIT|EXIT|EXIT|WINDOW']})

df = df.assign(EXIT_CNTR = lambda x: x.TYPE.apply(lambda y: y.split('|').count('EXIT')))
df = df.assign(WINDOW_CNTR = lambda x: x.TYPE.apply(lambda y: y.split('|').count('WINDOW')))
df = df.assign(FRONT_CNTR = lambda x: x.POSITION.apply(lambda y: y.split('|').count('FRONT')))
df = df.assign(BACK_CNTR = lambda x: x.POSITION.apply(lambda y: y.split('|').count('BACK')))

results in

enter image description here

Upvotes: 1

tmrlvi
tmrlvi

Reputation: 2361

The trick is to use collections.Counter

In [1]: from collections import Counter
In [2]: s = pd.Series(["AAA|BBB"])
In [3]: s.str.split("|").apply(Counter).apply(pd.Series)
Out[3]:    
   AAA  BBB
0    1    1

Though, you might also want to rename and concat them (assuming your DataFrame is called df):

# Counting
positions = df["POSITION"].str.split("|").apply(Counter).apply(pd.Series)
types = df["TYPE"].str.split("|").apply(Counter).apply(pd.Series)

# Tidying
positions = positions.fillna(0).add_suffix("_CNT")
types = types.fillna(0).add_suffix("_CNT")

# Joining
df = pd.concat([df, positions, types], axis=1)

Upvotes: 1

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