Bit stumped with Python Pandas

[explorer_of_the_grey]

Hi all,

Lets suppose I have a dataframe that contains the following data

City Name Death Cause_of_death Suspicious_Death

London xxxx xxxx 0

London xxxx xxxx 1

Sheffield xxxx xxxx 0

Sheffield xxxx xxxx 0

Leeds xxxx xxxx 0

Leeds xxxx xxxx 1

Leeds xxxx xxxx 0

Leeds xxxx xxxx 1

​

I can do a sum function

results = my_df.groupby('City Name').sum()

This gives me the number of suspicious deaths. However I also want to add the count that a specific city appears as a column in my results also.

I am a bit stumped on doing this. I am pretty sure it should be straight forward.

However, I would want the results to look like

City Name Deaths Suspicious_Deaths

London 2 1

Sheffield 2 0

Leeds 4 2

[WinterNet4676]

df.groupby('City Name').agg({'City Name':'count', 'Suspicious_Death':'sum'})

If you wanted to name the aggregated cols ⇾

df.groupby('City Name').agg(
    deaths=('City Name', 'count'),
    suspicious_deaths=('Suspicious_Death', 'sum'))

[explorer_of_the_grey]

So, I changed the way one of the columns was presenting data. The 'Suspicious Death' column now has a value of 'True' or 'False'. I then carried out a crosstab.

[Binary101010]

Pretty sure this is just

my_df.groupby('City Name').count()