Let's say my data looks like this:

How can I group the companies and get name and the number for the company with the biggest sum?

I want be able to print something like :

Facebook was mentioned in the news the most - 24 times.

I tried this but it did not work the way I wanted:

df.groupby("company").sum()

CodePudding user response：

Use value_counts:

>>> df.company.value_counts().head(1)
Facebook    3
Name: company, dtype: int64

Update:

Could you please tell me how I could go about printing it out in a sentence?

company, count = list(df.company.value_counts().head(1).items())[0]
print(f'{company} was mentioned in the news the most - {count} times.')

# Output:
Facebook was mentioned in the news the most - 3 times.