My dataframe looks like this
df = pd.Dataframe({ 'a': ["10001", "10001", "10002", "10002" , "10002"], 'b': ['hello', 'hello', 'hola', 'hello', 'hola']})
I want to create a new column 'c' of boolean values with the following condition:
My current code is the following:
def check_consistency(col1,col2):
df['match'] = df[col1].eq(df[col1].shift())
t = []
for i in df['match']:
if i == True:
t.append(df[col2].eq(df[col2].shift()))
check_consistency('a','b')
And it returns error.
I think this is groupby
df.groupby('a').b.apply(lambda x : x==x.shift())
Out[431]:
0 False
1 True
2 False
3 False
4 False
Name: b, dtype: bool
A bitwise &
should do: Checking if both the conditions are satisfied:
df['c'] = (df.a == df.a.shift()) & (df.b == df.b.shift())
df.c
#0 False
#1 True
#2 False
#3 False
#4 False
#Name: c, dtype: bool
Alternatively, if you want to make your current code work, you can do something like (essentially doing the same check as above):
def check_consistency(col1,col2):
df['match'] = df[col1].eq(df[col1].shift())
for i in range(len(df['match'])):
if (df['match'][i] == True):
df.loc[i,'match'] = (df.loc[i, col2] == df.loc[i-1, col2])
check_consistency('a','b')
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