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I have an IPL Data Set called matches.csv which I am fetching from Kaggle, from where I am trying to find out the place where the maximum number of matches were played.

The below code is giving me the correct value for the number of matches played, but I would like to check the Name of the Stadium where the maximum number of matches were played.

matches['venue'].value_counts().max()

This gives me 66

Expected Output is to be like: 

M Chinnaswamy Stadium     66

Also if it is possible I would like to get all the details of the last match that was played in that Stadium.

Below is the head of the dataframe:

    id  season  city    date    team1   team2   toss_winner toss_decision   result  dl_applied  winner  win_by_runs win_by_wickets  player_of_match venue   umpire1 umpire2 umpire3
0   1   2017    Hyderabad   2017-04-05  Sunrisers Hyderabad Royal Challengers Bangalore Royal Challengers Bangalore field   normal  0   Sunrisers Hyderabad 35  0   Yuvraj Singh    Rajiv Gandhi International Stadium, Uppal   AY Dandekar NJ Llong    NaN
1   2   2017    Pune    2017-04-06  Mumbai Indians  Rising Pune Supergiant  Rising Pune Supergiant  field   normal  0   Rising Pune Supergiant  0   7   SPD Smith   Maharashtra Cricket Association Stadium A Nand Kishore  S Ravi  NaN
2   3   2017    Rajkot  2017-04-07  Gujarat Lions   Kolkata Knight Riders   Kolkata Knight Riders   field   normal  0   Kolkata Knight Riders   0   10  CA Lynn Saurashtra Cricket Association Stadium  Nitin Menon CK Nandan   NaN
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  • Possible duplicate of Find maximum value of a column and return the corresponding row values using Pandas Commented Jan 6, 2019 at 14:38
  • @busybear, I dont think it's exactly a duplicate. Here he wants the max row from value_counts(). Do you agree? Commented Jan 6, 2019 at 14:41
  • @najeem Yes, but the value_counts result is still a dataframe. Although I did just notice the last bit where OP asks for information from the last match, which would require a bit more information as you pointed out. Commented Jan 6, 2019 at 14:45
  • @jezrael can we have this open now? Commented Jan 7, 2019 at 18:21
  • 1
    @anky_91 I cannot do it, only moderator. Vote for opening. Commented Jan 7, 2019 at 20:22

2 Answers 2

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Find out the place where the maximum number of matches were played

>>matches['venue'].value_counts().head(1)
M Chinnaswamy Stadium    66

Note that value_counts already sorts the data in a descending manner, so the first record is always the maximum.

Get all the details of the last match that was played in that Stadium.

>>matches[matches['venue']=='M Chinnaswamy Stadium'].sort_values('date',ascending=False).head(1)

    id  season  city    date    team1   team2   toss_winner toss_decision   result  dl_applied  winner  win_by_runs win_by_wickets  player_of_match venue   umpire1 umpire2 umpire3
57  58  2017    Bangalore   2017-05-19  Kolkata Knight Riders   Mumbai Indians  Mumbai Indians  field   normal  0   Mumbai Indians  0   6   KV Sharma   M Chinnaswamy Stadium   NJ Llong    Nitin Menon NaN

Here you can make a slice of the dataframe by querying the venue name, and then sort_values on the date column putting ascending=False and getting the first result, which gives you the latest match details.

Note I have used the latest kaggle dataset. The values might have changed, but the solution remains same.

Hope this helps.

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Move the value_counts() to a new variable and then you can extract a subset of that data. 

vmax = matches['venue'].value_counts()
vmax[vmax == vmax.max()]

Also if it is possible I would like to get all the details of the last match that was played in that Stadium.

For this, you need to post sample of the dataset.

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