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I have a pandas dataframe like this:
Year Winner
4 1954 Germany
9 1974 Germany
13 1990 Germany
19 2014 Germany
5 1958 Brazil
6 1962 Brazil
8 1970 Brazil
14 1994 Brazil
16 2002 Brazil
How to plot the frequency count of column Winner, so that y axis has frequency and x-axis has name of country?
I tried:
import numpy as np
import pandas as pd
df.groupby('Winner').size().plot.hist()
df1['Winner'].value_counts().plot.hist()
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In pandas you can get the count of the frequency of a value that occurs in a DataFrame column by using Series. value_counts() method, alternatively, If you have a SQL background you can also get using groupby() and count() method.
Note: You also can use this formula =COUNTIF(A1:A10,"AAA-1") to count the frequency of a specific value. A1:A10 is the data range, and AAA-1 is the value you want to count, you can change them as you need, and with this formula, you just need to press Enter key to get the result.
To create a frequency column for categorical variable in an R data frame, we can use the transform function by defining the length of categorical variable using ave function. The output will have the duplicated frequencies as one value in the categorical column is likely to be repeated.
You are close, need Series.plot.bar because value_counts already count frequency:
df1['Winner'].value_counts().plot.bar()
Also working:
df1.groupby('Winner').size().plot.bar()
Difference between solutions is output of value_counts will be in descending order so that the first element is the most frequently-occurring element.
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