Manipulating csv data file using python

Question

I want to work with data of NBA. That is why I have to make comparison. I need to get home win percentage. However it cannot convert string to int.

results["HomeWin"]=int(results["Home Team"])<int(results["OT?"])
y_true=results["HomeWin"].values
print("Home win percentage is{0:.1f}%".format(100*results["HomeWin"].sum()/results["HomeWin"].count()))

error is:cannot convert the series to type 'int'

use astype(int) : results["HomeWin"]=results["Home Team"].astype(int)<results["OT?"].astype(int) — EdChum
– EdChum, Commented Jul 26, 2016 at 8:09

jezrael · Accepted Answer · 2016-07-26 08:23:41Z

1

You need cast by Series.astype string numbers to int:

results["HomeWin"] = results["Home Team"].astype(int) < results["OT?"].astype(int)

Sample:

import pandas as pd

results = pd.DataFrame({'Home Team':['1','2','3'],
                   'OT?':['4','2','1']})

print (results)
  Home Team OT?
0         1   4
1         2   2
2         3   1


results["HomeWin"] = results["Home Team"].astype(int) < results["OT?"].astype(int)
print (results)
  Home Team OT?   HomeWin
0         1   4      True
1         2   2     False
2         3   1     False

edited Jul 26, 2016 at 8:23

answered Jul 26, 2016 at 8:09

jezrael

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3 Comments

fallen Over a year ago

it gives error as: invalid literal for long() with base 10: 'November'

jezrael Over a year ago

There is problem you have string data in columns like November which cannot be converted to number. You can check this problematic values by

print (results.ix[pd.to_numeric(results["Home Team"], errors='coerce').isnull() | pd.to_numeric(results["OT?"], errors='coerce').isnull(), ['Home Team','OT?']])

jezrael Over a year ago

You can check it by results = pd.DataFrame({'Home Team':['1','2','3', 'November'], 'OT?':['4','September','1', '5']})

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