How to compare two columns of the same dataframe?

Question

I have a dataframe like this:

 match_id inn1  bat  bowl  runs1 inn2   runs2   is_score_chased
    1     1     KKR  RCB    222  2      82          1
    2             


        

Answer 1

This is a good case for using apply.

Here there is an example of using apply on two columns.

You can adapt it to your question with this:

def f(x):    
   return 'yes' if x['run1'] > x['run2'] else 'no'

df['is_score_chased'] = df.apply(f, axis=1)

However, I would suggest filling your column with booleans so you can make it more simple

def f(x):    
   return x['run1'] > x['run2']

And also using lambdas so you make it in one line

df['is_score_chased'] = df.apply(lambda x: x['run1'] > x['run2'], axis=1)

Answer 2

You can more easily use np.where.

high_scores1['is_score_chased'] = np.where(high_scores1['runs1']>=high_scores1['runs2'], 
                                           'yes', 'no')

Typically, if you find yourself trying to iterate explicitly as you were to set a column, there is an abstraction like apply or where which will be both faster and more concise.

Answer 3

You need to reference the fact that you are iterating through the dataframe, so;

for i in (high_scores1):
  if(high_scores1['runs1'][i]>=high_scores1['runs2'][i]):
      high_scores1['is_score_chased'][i]='yes'
  else:
      high_scores1['is_score_chased'][i]='no'