I'm trying to visually compare two columns in a data frame and it either makes a weird table with 'frequency' instead of one of the columns

I tried these options:

ct1=pd.crosstab(df['releaseyear'],df['score'],normalize=True)
ct1.plot()

df.plot( x='releaseyear', y='score', kind='hist')

and also a scatter plot which get the x and y right but I don't know how normalize it so it will only show the average of each year and not all the data

plt.scatter(df['releaseyear'], df['score'])
plt.show()

CodePudding user response：

There is no proper data which can be used to reproduce the dataframe or clue about how dataframe looks.

This answer is according to what i understood if data is like this

   year score
   2001 20
   2001 18
   2002 12
   2002 16

then first use groupby and group data according to year and apply required aggregate function.

df=df.groupby('year').mean().reset_index()

output

   year  score
0  2001   19.0
1  2002   14.0

you can then plot the data accordingly.