CODEWITHSUNDEEP
pythonpandasif-statementdataframeapply
DevEx
DevEx

Reputation: 4571

Pandas dataframe If else with logical AND involving two columns

How to add logical AND in a control statement involving two columns of a pandas dataframe i.e.

This works:

def getContinent(row):
    if row['Location'] in ['US','Canada']:
        val = 'North America'
    elif row['Location'] in['UK', 'Germany']:
        val = 'Europe'
    else:
        val = None
    return val

df.apply(getContinent, axis=1)

Now I want to include an additional condition with another field row['Sales']:

def getContinent(row):
    if row['Location'] in ['US','Canada'] & row['Sales'] >= 100:
        val = 'North America'
    elif row['Location'] in['UK', 'Germany'] & row['Sales'] < 100:
        val = 'Europe'
    else:
        val = None
    return val

df.apply(getContinent, axis=1)

ValueError: ('Arrays were different lengths: 6132 vs 2', u'occurred at index 0')

Upvotes: 1

Views: 5411

Answers (1)

jezrael
jezrael

Reputation: 863651

You need use and instead &:

df = pd.DataFrame({'Sales': {0: 400, 1: 20, 2: 300}, 
                   'Location': {0: 'US', 1: 'UK', 2: 'Slovakia'}})
print (df)

   Location  Sales
0        US    400
1        UK     20
2  Slovakia    300

def getContinent(row):
    if row['Location'] in ['US','Canada'] and row['Sales'] >= 100:
        val = 'North America'
    elif row['Location'] in['UK', 'Germany'] and row['Sales'] < 100:
        val = 'Europe'
    else:
        val = None
    return val

print (df.apply(getContinent, axis=1))
0    North America
1           Europe
2             None
dtype: object

Upvotes: 4

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