CODEWITHSUNDEEP
pythonpandasdataframe
milka1117
milka1117

Reputation: 521

Values in one column based on condition in another column

I have a dataframe:

Data = {'group':  ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l'],
        'value1': [2, 0, 0, 5, 5, 5, 6, 31, 7, 5, 0, 99],
        'value2': [25, 12 ,15, 11, 36, 3, 65, 6, 89, 8, 74, 5]
        }

current_result = pd.DataFrame(Data, columns = ['group','value1', 'value2'])

I want to set value2 to zero if corresponding value1 is equal to zero while keeping all other values the same. So my desired result would be:

Data = {'group':  ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l'],
        'value1': [2, 0, 0, 5, 5, 5, 6, 31, 7, 5, 0, 99],
        'value2': [25, 0 ,0, 11, 36, 3, 65, 6, 89, 8, 0, 5]
        }

current_result = pd.DataFrame(Data, columns = ['group','value1', 'value2'])

How could I do this?

Upvotes: 0

Views: 917

Answers (6)

shaoleen00
shaoleen00

Reputation: 13

def change_value(row):
    if row.value1 == 0:
        row.value2 = 0
    return row


current_result = current_result.apply(change_value, axis=1)

Upvotes: 0

Pallavi Sharma
Pallavi Sharma

Reputation: 140

Use this:

current_result.loc[current_result['value1'] == 0, ['value2']] = 0

Upvotes: 1

jfaccioni
jfaccioni

Reputation: 7539

Without using any Pandas core features, this loop gets the job done:

for index, value in enumerate(current_result["value1"]):
    if value == 0:
        current_result["value2"][index] = 0

Upvotes: 0

jezrael
jezrael

Reputation: 863741

You can multiple by boolean mask - True are processes like 1,False like 0 so compare for not equal 0 by Series.ne:

current_result['value2'] *= current_result['value1'].ne(0)
print (current_result)
   group  value1  value2
0      a       2      25
1      b       0       0
2      c       0       0
3      d       5      11
4      e       5      36
5      f       5       3
6      g       6      65
7      h      31       6
8      i       7      89
9      j       5       8
10     k       0       0
11     l      99       5

Upvotes: 2

Jeril
Jeril

Reputation: 8561

current_result.loc[current_result['value1'] == 0, 'value2'] = 0

Upvotes: 0

anky
anky

Reputation: 75150

Use df.loc[]

current_result.loc[current_result.value1.eq(0),'value2']=current_result.value1
print(current_result)

   group  value1  value2
0      a       2      25
1      b       0       0
2      c       0       0
3      d       5      11
4      e       5      36
5      f       5       3
6      g       6      65
7      h      31       6
8      i       7      89
9      j       5       8
10     k       0       0
11     l      99       5

Upvotes: 2

Related Questions