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In [2]:
!pip install jovian --upgrade --quiet
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!pip install pandas --upgrade
Requirement already up-to-date: pandas in /srv/conda/envs/notebook/lib/python3.7/site-packages (1.1.2) Requirement already satisfied, skipping upgrade: pytz>=2017.2 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas) (2020.1) Requirement already satisfied, skipping upgrade: python-dateutil>=2.7.3 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas) (2.8.1) Requirement already satisfied, skipping upgrade: numpy>=1.15.4 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas) (1.19.2) Requirement already satisfied, skipping upgrade: six>=1.5 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas) (1.15.0)
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import pandas as pd
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matches_raw_df = pd.read_csv('matches.csv')
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matches_raw_df
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matches_raw_df.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 756 entries, 0 to 755 Data columns (total 18 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 id 756 non-null int64 1 season 756 non-null int64 2 city 749 non-null object 3 date 756 non-null object 4 team1 756 non-null object 5 team2 756 non-null object 6 toss_winner 756 non-null object 7 toss_decision 756 non-null object 8 result 756 non-null object 9 dl_applied 756 non-null int64 10 winner 752 non-null object 11 win_by_runs 756 non-null int64 12 win_by_wickets 756 non-null int64 13 player_of_match 752 non-null object 14 venue 756 non-null object 15 umpire1 754 non-null object 16 umpire2 754 non-null object 17 umpire3 119 non-null object dtypes: int64(5), object(13) memory usage: 106.4+ KB
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import jovian
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jovian.commit(files = ['matches.csv'])
[jovian] Attempting to save notebook..
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matches_raw_df.groupby('season').season.count()
Out[25]:
season
2008    58
2009    57
2010    60
2011    73
2012    74
2013    76
2014    60
2015    59
2016    60
2017    59
2018    60
2019    60
Name: season, dtype: int64
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matches_raw_df.groupby('season').toss_decision.value_counts() / matches_raw_df.groupby('season').season.count()
--------------------------------------------------------------------------- NameError Traceback (most recent call last) <ipython-input-1-83ad5ba3f4d1> in <module> ----> 1 matches_raw_df.groupby('season').toss_decision.value_counts() / matches_raw_df.groupby('season').season.count() NameError: name 'matches_raw_df' is not defined
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(matches_raw_df.team2.value_counts() + matches_raw_df.team1.value_counts())

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matches_raw_df.winner.value_counts() / (matches_raw_df.team2.value_counts() + matches_raw_df.team1.value_counts())
Out[15]:
Chennai Super Kings            0.609756
Deccan Chargers                0.386667
Delhi Capitals                 0.625000
Delhi Daredevils               0.416149
Gujarat Lions                  0.433333
Kings XI Punjab                0.465909
Kochi Tuskers Kerala           0.428571
Kolkata Knight Riders          0.516854
Mumbai Indians                 0.582888
Pune Warriors                  0.260870
Rajasthan Royals               0.510204
Rising Pune Supergiant         0.625000
Rising Pune Supergiants        0.357143
Royal Challengers Bangalore    0.466667
Sunrisers Hyderabad            0.537037
dtype: float64
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jovian.commit()
[jovian] Attempting to save notebook.. [jovian] Updating notebook "srijansrj5901/ipl-data-anaysis-78bb0" on https://jovian.ml/ [jovian] Uploading notebook.. [jovian] Capturing environment.. [jovian] Committed successfully! https://jovian.ml/srijansrj5901/ipl-data-anaysis-78bb0
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jovian.commit(files = ['matches.csv'])
[jovian] Attempting to save notebook.. [jovian] Updating notebook "srijansrj5901/ipl-matches-data-analysis" on https://jovian.ml/ [jovian] Uploading notebook.. [jovian] Capturing environment.. [jovian] Uploading additional files... [jovian] Committed successfully! https://jovian.ml/srijansrj5901/ipl-matches-data-analysis
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