using the dataframe code at this link https://pastebin.com/d1aW7u5N
I grouped it like this df.groupby([col, 'win']).count()
to achieve this output
But I want to have it be for every death
, display the percentage of win/(win+loss) (basically show the win percentage) using the match id
For example, the end dataframe would look as such:
(deaths, percentage),
(0, 1) because 9 wins and 0 losses for deaths=0
(1, .77) because 7 wins and 2 losses for deaths=1 and 7/(7+2) = .77
(2, .84) because 21 wins and 4 losses for deaths=2 and 21/(21+4) = .84
(3, .74) ...
Problem: I want to display the winrates per deaths as outlined above, thanks
This was my final answer that allowed me to see the winrates (percentage within each group) for all values
df = df.groupby([col, 'win']).count().reset_index().pivot('deaths', 'win', 'matchID')
df[0] = np.nan_to_num(df[0])
df[1] = np.nan_to_num(df[1])
df['winrate'] = (df[1] / (df[1] + df[0]))
df.columns.name = None
df = df.drop([0, 1], axis=1)
df
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