How to find the total runs for every match (Can be understood by match_id and innings)

Question

df=pd.read_csv('./ipl/all_matches.csv')
df1=df[['match_id','season','venue','innings','striker','bowler','batting_team','bowling_team','ball','runs_off_bat','extras']]

df1=df1.loc[(df1['ball'] < 6.1)]
df1['total'] = df1['runs_off_bat'] + df1['extras']

The data frame should look like

you want to group by the match id and sum the runs. have a look at: [pandas groupby and sum](https://stackoverflow.com/q/39922986/13138364) — tdy, May 01 '21 at 08:00
Does this answer your question? [Pandas group-by and sum](https://stackoverflow.com/questions/39922986/pandas-group-by-and-sum) — bad_coder, May 02 '21 at 09:35

score 0 · Answer 1 · edited May 01 '21 at 19:13

0

Few changes that I've made:

Specify the columns that you wanna read in the pd.read_csv args.
groupby match_id and aggregated the sum of the total column for each group.

use_col = ['match_id','season','venue','innings','striker','bowler','batting_team','bowling_team','ball','runs_off_bat','extras']
df=pd.read_csv('./ipl/all_matches.csv', usecols= use_col)

df1=df1.loc[(df1['ball'] < 6.1)]
df1['total'] = df1['runs_off_bat'] + df1['extras']
total_run_per_match = df1.groupby('match_id').agg({'total': sum})

If you wanna preserve the original data frame:

df1['total_run_per_match'] = df1.groupby('match_id')['transform'].sum()

edited May 01 '21 at 19:13

desertnaut

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answered May 01 '21 at 08:19

Nk03

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But I want to store that total in that dataframe itself.So how can i do that – SOUVIK GHOSH May 01 '21 at 08:29
Wrong number of items passed 3, placement implies 1 ----the above code generates this error – SOUVIK GHOSH May 01 '21 at 09:34

How to find the total runs for every match (Can be understood by match_id and innings)

1 Answers1