Reputation: 6488
I have a data frame with a column tfidf_sorted
as follows:
tfidf_sorted
0 [(morrell, 45.9736796), (football, 25.58352014...
1 [(melatonin, 48.0010051405), (lewy, 27.5842077...
2 [(blues, 36.5746634797), (harpdog, 20.58669641...
3 [(lem, 35.1570832476), (rottensteiner, 30.8800...
4 [(genka, 51.4667410433), (legendaarne, 30.8800...
The type(df.tfidf_sorted)
returns pandas.core.series.Series
.
This column was created as follows:
df['tfidf_sorted'] = df['tfidf'].apply(lambda y: sorted(y.items(), key=lambda x: x[1], reverse=True))
where tfidf
is a dictionary.
How do I get the first 10 key-value pairs from tfidf_sorted
?
Upvotes: 8
Views: 36969
Reputation: 862911
IIUC you can use:
from itertools import chain
#flat nested lists
a = list(chain.from_iterable(df['tfidf_sorted']))
#sorting
a.sort(key=lambda x: x[1], reverse=True)
#get 10 top
print (a[:10])
Or if need top 10 per row add [:10]
:
df['tfidf_sorted'] = df['tfidf'].apply(lambda y: (sorted(y.items(), key=lambda x: x[1], reverse=True))[:10])
Upvotes: 4