Creating multiple lists in a for-loop

Question

I read in information from a pandas dataframe. The column "keywords" can but doesn't have to contain comma-seperated keywords for which I later on want to search for in a text. This part is easy if I only have one list of keywords over which I iterate and then look for in the text. However, I need a list for every row. How do I do that?

The input is the following Dataframe (df):

Search  keywords
 1      Smurf, gummybear, Echo
 2      Blue, yellow, red
 3      Apple, Orange, Pear

l_search = df['search'].tolist()
l_kw = df['keywords'].tolist()

Now I have a list of lists of keywords. I want to split that up into as many lists as I have searches, basically:

i = 1
for s in l_search:
   l_kw_i = [] # here the list would be l_kw_1, then l_kw_2, ...
   l_kw_i.append(s)
   i = i+1
# l_kw_1 would be now "Smurf, gummybear, Echo".

After that I would like to split each list at the commas, so l_kw_1 would now contain "Smurf", "gummybear", "Echo". I would then interate over the results of each search and the respective list to determine if at least one keyword appears.

The main problem is to create a variable amount of lists of keywords based on how many searches there are.

Use a dict to store the list for the row.... You can even defaultdict so that the list is always initialized — tehhowch
– tehhowch, Commented Jul 17, 2019 at 13:51
Possible duplicate of Changing variable names with Python for loops — Vikramaditya Gaonkar
– Vikramaditya Gaonkar, Commented Jul 17, 2019 at 13:55
Possible duplicate of How do I create a variable number of variables? — Akaisteph7
– Akaisteph7, Commented Jul 17, 2019 at 14:01

marc_s · Accepted Answer · 2019-10-04 20:22:35Z

0

The trick is to use a dictionary. You can do it in one line using a dictionary comprehension combined with a list comprehension :

df = pd.DataFrame({'Search':[1,2,3], 
                   'keywords' : ["Smurf, gummybear, Echo", "Blue, yellow, red", "Apple, Orange, Pear"] })

l_kw = {i:[y for y in x['keywords'].split(',')] for i, x in df.iterrows()}

Output :

{0: ['Smurf', ' gummybear', ' Echo'],
 1: ['Blue', ' yellow', ' red'],
 2: ['Apple', ' Orange', ' Pear']}

edited Oct 4, 2019 at 20:22

marc_s

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answered Jul 17, 2019 at 14:20

vlemaistre

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