Pandas Part 12 - Groupby on IPL Dataset

[@gurpartapsandhu94]

views dont justify your hardwork and ease with which you teach

[@campusx-official]

Sach me sir :(

[@rahulgiri9880]

Superb explanation. Not easy to explain that so simply. Appreciate you for sharing your great wisdom & knowledge.

[@shaikusman536]

Awsome explanation Guruji...Respect from bangalore.

[@princeking370]

its the best video i have seen on you tube 🔥🔥🔥

[@pravinshende.DataScientist]

by watching your vedios , every time getting new glimses ...and it helping me to enrich my knowledge..for data science!! thank a lots!

[@kanakkanak1520]

BEST!! you are the best teacher!

[@sujithsaikalakonda4863]

Great lecture sir. Lot of respect.

[@GaganDeep-mj5hi]

Thank you sir for video. You have cleared all the logics and doubts.

[@prathmeshdesai4480]

Hi Sir, thank you so much for the wonderful explanation. Was very helpful. Also would like to point out a small mistake. While accessing max number of 4's or 6's, there had to be a condition that the score was with single ball, other wise, there are batsman scoring 4 with multiple balls too. Sharing correct code below deli[deli['ball']==1][deli['batsman_runs']==4].groupby('batsman').sum().sort_values('batsman_runs',ascending=False).head()

[@rakeshnagarkar8759]

The code which provided by the campusx is correct. if you check the dataset carefully it is clearly mention that for each ball there is a separete batsman_run column(row)

[@abhayrana5965]

Those students are blessed!

[@Darkwolf9280]

13:56 method 2: # Mask to filter only the rows where batsman scored 6 mask = delivery['batsman_runs'] == 6 new_delivery = delivery[mask] # Count the number of times each batsman hit a 4 top_batsmen_sixes = new_delivery['batsman'].value_counts().head() top_batsmen_sixes

[@smitrathod2330]

Best lect. Sir hats off 😁👍👍

[@life3.088]

accept too much love from us i mean from pakistan student who follow u

[@dikshagupta3276]

On which domain pls suggest .nice explanation

[@zkhan2023]

The whole video is good but can you please share the last line of code where you have added an index zero. but the rest was good

[@truth4indiabyram952]

def runs_Scored(batsman_name): VK = data[data['batsman'] == batsman_name] return VK.groupby("bowling_team")["batsman_runs"].sum().sort_values(ascending=False).index[0]

[@RSVERMA948]

@@truth4indiabyram952 thankxx buddy

[@Mjeditz87]

Konsa website per career section me jana hain sir cricket me bhi post dekhne ke liye

[@talkswithRishabh]

awesome explanation thanks sir

[@Mjeditz87]

Sir,Can we use nlargest(5) instead of sort_values() for finding top 5 bats_man

[@life3.088]

u r my great sir

[@sriyansh3237]

Dataset not available. Now how will I continue?

[@30yuvrajingale48]

bro they have provided the link

[@sriyansh3237]

@@30yuvrajingale48 where?

[@30yuvrajingale48]

keep it up and all the best!!!

[@nehasen7313]

sir i am unable to read the file...it is showing ( UnicodeDecodeError: 'utf-8' codec can't decode byte 0xcb in position 10: invalid continuation byte )

[@TarunSharma-js8tf]

Use r'(path)

[@khanaslam5722]

Sir ap ke file hack hu rahe hai kaggle se download ke hai

[@abdulwasay8540]

how to calculate that which team has conceded most runs

[@abdulwasay8540]

mask3 = delivery.groupby("bowling_team") mask3["total_runs"].sum().sort_values(ascending = False).head(5) Thank me later.

[@rahulstudies1178]

sir how to find most wickets using this deliveries.csv ?

[@sabalniroula26]

data = pd.read_csv("deliveries.csv") mask1 = data['dismissal_kind'] == 'caught' mask2 = data['dismissal_kind'] == 'bowled' mask3 = data['dismissal_kind'] == 'caught and bowled' mask4 = data['dismissal_kind'] == 'run out' mask5 = data['dismissal_kind'] == 'lbw' mask6 = data['dismissal_kind'] == 'stumped' mask7 = data['dismissal_kind'] == 'retired hurt' mask8 = data['dismissal_kind'] == 'hit wicket' mask9 = data['dismissal_kind'] == 'obstructing the field' d=data.groupby('dismissal_kind') d= data[mask1 | mask2 | mask3 | mask4 | mask5 | mask6 | mask7 | mask8 | mask9 ] d['bowler'].value_counts().sort_values(ascending=False).head(5)

[@Apurvadidisorts]

Unable to run the csv file after so many attempts. Please give me solution.

[@Apurvadidisorts]

Its showing 'UnicodeDecodeError '

[@surajmamidwar9556]

please share the code for maximum century from dataframe

[@ahmadhussain6615]

total=data.groupby(['batsman','match_id'])['batsman_runs'].sum().reset_index() mask2=total['batsman_runs']>=50 fifty=total[mask2] fifty.groupby('batsman').count().sort_values('batsman_runs',ascending=False)

[@killerelite7841]

runs.get_group('V Kohli').shape - this line doesn't represent ball played ball V Kohli but we can get the balls by - runs['ball'].sum() or runs.get_group('V Kohli')['ball'].sum() . It gives sum of the ball's played by the players. If i am wrong plz comment.

[@amarmallick79]

is the dataset available?

[@animeshbasak490]

def maxscored(batsman_name): vk=df[df['batsman']==batsman_name] return vk.groupby('bowling_team')['batsman_runs'].sum().sort_values(ascending=False).index[0] sir can you please tell me why I'm getting error on index[0]

[@prathmeshdesai4480]

This code is correct. I ran the same code its working. check if you are using the correct data(csv file) or copy paste the entire error message in chatgpt. Hope this helps

[@MRAgundli]

I have same problem bro , did you get tackle ?

[@yashkumariitdelhi6363]

@@MRAgundli just remove the commas from the variable batsman_name

[@rockeveryday5823]

df[df['batsman_runs']==4].value_counts('batsman').head()