key_words_to_search = ['hello', 'goodbye']
df = pd.DataFrame({
'col1':['hello','hi','ciao'],
'col2':['hello panda','goodbye','bonjour'],
'col3':['ni hao','hola','hello']})
I've been using something like the below, but not sure how to get the actual name of the column. Thanks!
mask = df.applymap(lambda x: word in str(word).lower())
temp = df[mask.any(axis=1)].copy()
Here's a way of doing:
d = []
for k in key_words_to_search:
print(k)
i = df.applymap(lambda x: k in x)
i = i.astype(int).mask(i, i.columns.to_series(), axis=1).astype(str).agg(lambda x: ','.join(i for i in x if not i.isdigit()), 1)
d.append(i)
df[['hello','goodbye']] = pd.concat(d, axis=1)
print(df)
col1 col2 col3 hello goodbye
0 hello hello panda ni hao col1,col2
1 hello panda goodbye hola col1 col2
2 ni hao goodbye hello col3 col2
import pandas as pd
key_words_to_search = ['hello', 'x']
df = pd.DataFrame({
'col1':['hello','hi','ciao', 'x'],
'col2':['hello panda','goodbye','bonjour', 'f'],
'col3':['ni hao','hola','hello', 'a']})
cols = list(map(lambda col_name: (col_name, any(x in df[col_name].unique() for x in key_words_to_search)), list(mask.columns)))
res = list(map(lambda item: item[0], list(filter(lambda c: c[1], cols))))
print(res)
