How to map sevaral keywords with a dataframe column values using pandas in python

Question

Hi I have a list of keywords.

keyword_list=['one','two']

DF,

    Name      Description
    Sri       Sri is one of the good singer in this two
    Ram       Ram is one of the good cricket player

I want to find the rows which are having all the values from my keyword_list.

my desired output is,

output_Df,
    Name    Description
    Sri     Sri is one of the good singer in this two

I tried, mask=DF['Description'].str.contains() method but I can do this only for a single word pls help.

jezrael · Accepted Answer · 2017-10-03 06:55:22Z

2

Use np.logical_and + reduce of all masks created by list comprehension:

keyword_list=['one','two']

m = np.logical_and.reduce([df['Description'].str.contains(x) for x in keyword_list])
df1 = df[m]
print (df1)

  Name                                Description
0  Sri  Sri is one of the good singer in this two

Alternatives for mask:

m = np.all([df['Description'].str.contains(x) for x in keyword_list], axis=0)

#if no NaNs
m = [set(x.split()) >= set(keyword_list) for x in df['Description']]

edited Oct 3, 2017 at 6:55

answered Oct 3, 2017 at 6:38

jezrael

868k103 gold badges1.4k silver badges1.3k bronze badges

Sign up to request clarification or add additional context in comments.

3 Comments

Pyd Over a year ago

your solution for the above question is working fine, could you please suggest me best tutorials for numpy and pandas as I want to be good with it.

jezrael Over a year ago

Hard question, in my opinion the best are pandas documentation and tutorials, especially I like modern pandas.

Pyd Over a year ago

I did. I was told to wait for sometime to accept it.

Collectives™ on Stack Overflow

How to map sevaral keywords with a dataframe column values using pandas in python

1 Answer 1

3 Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

3 Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related