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I have text reviews in one column in Pandas dataframe and I want to count the N-most frequent words with their frequency counts (in whole column - NOT in single cell). One approach is Counting the words using a counter, by iterating through each row. Is there a better alternative?
Representative data.
0 a heartening tale of small victories and endu 1 no sophomore slump for director sam mendes w 2 if you are an actor who can relate to the sea 3 it's this memory-as-identity obviation that g 4 boyd's screenplay ( co-written with guardian 
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To get the most frequent value of a column we can use the method mode . It will return the value that appears most often. It can be multiple values.
How do you Count the Number of Occurrences in a data frame? To count the number of occurrences in e.g. a column in a dataframe you can use Pandas value_counts() method. For example, if you type df['condition']. value_counts() you will get the frequency of each unique value in the column “condition”.
To count the frequency of a value in a DataFrame column in Pandas, we can use df. groupby(column name). size() method.
Using the size() or count() method with pandas. DataFrame. groupby() will generate the count of a number of occurrences of data present in a particular column of the dataframe.
from collections import Counter Counter(" ".join(df["text"]).split()).most_common(100) im pretty sure would give you what you want (you might have to remove some non-words from the counter result before calling most_common)
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