Conditions on a DF or Series.?-CodePudding

Hi I imported a dataset called train and selected "Sex" from this list.

But I couldn't use the if statement on it. I get the following error :

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I have already tried changing it to string datatype but without result.

What can i do to fix this? Changing it to a DF doesnt help same error.

import numpy as np



Sex = train['Sex']


for x in Sex : 
    if Sex == "male" :
        SurvBi = 0
    else :
        SurBi = 1

CodePudding user response：

this solution may help

import pandas as pd

train = {
  "Sex": ["male","female"],
}
Sex = train['Sex']
for x in Sex:

    SurvBi = 0 if x == "male" else 1
    print(SurvBi)

CodePudding user response：

Note to always check your formatting before posting your question so people have more time to solve your problem than to reconstruct your problem.

Assuming you know how to create a pandas DataFrame out of your data, this approach will work.

for index, row in df.iterrows():

    if row == "male":
        SurvBi = 0
    elif row == "female":
        SurBi = 1
    else: 
        print("invalid")

CodePudding user response：

if you want to check value for every row separatelly then you should use x == 'male'

for x in train.Sex: 
    if x == "male":
        SurBi = 0
    else:
        SurBi = 1
    print(x, SurBi)

or you can use fact that int(True) gives 1, and int(False) gives 0

for x in train.Sex:
    SurBi = int(x != "male")
    print(x, SurBi)

But if you want to use all results later then you should keep them on list

all_results = [] 

for x in train.Sex: 
    if x == "male":
        SurBi = 0
    else:
        SurBi = 1
    print(x, SurBi)
    all_results.append( SurBi )

but it would be simpler to do

all_results = (train.Sex != "male").astype(int).to_list()

But if you want to check for all column at once then you have to remember that panda (and numpy) works on vector/matrix and comparition gives also vector/matrix like [True, False, ...] but if needs single result True or False - and you have to use any( Sex == "male" ) or all( Sex == "male" ) to get single value

if any( Sex == "male" ):
   print('At least one person is male')

if all( Sex == "male" ):
   print('All persons are male')