dups_df = df.pivot_table(columns=['DstAddr'], aggfunc='size')
print (dups_df )

I am using this code block to show the duplicates but I would like to see the output in order(most used one) and maybe with a better visualization. How can I do this?

CodePudding user response：

You can use the duplicated method, as show above:

print(df[df.duplicated(subset='DstAddr')]

You can see the whole documentation at https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.duplicated.html

Other way is value_counts method, as show above too:

print(df.value_counts(subset='DstAddr', ascending=False))

Documentation at https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.value_counts.html

To vizualize this, I you can you value_counts and add a plot method.

df.value_counts(subset='DstAddr', ascending=False).plot()

Documentation at https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.html

CodePudding user response：

you can use the duplicated() method. This method returns a Boolean values for each row:

Example Returns True for every row that is a duplicate, otherwise False:

print(df.duplicated())

or if want to remove all duplicates you can use drop_duplicates() method.

df.drop_duplicates(inplace = True)

CodePudding user response：

You can use:

df.DstAddr.value_counts()

and:

df.DstAddr.value_counts().plot(kind='bar')