pandas: search column values from one df in another df column that contains lists - python-3.x

Question

I need to search the values from the df1['numsearch'] column into the lists in df2['Numbers']. If the number is in those lists, then I want to add values from the df2['Score'] column to df1. See desired output below.
df1 = pd.DataFrame(
{'Day':['M','Tu','W','Th','Fr','Sa','Su'],
'numsearch':['1','20','14','99','19','6','101']
})
df2 = pd.DataFrame(
{'Letters':['a','b','c','d'],
'Numbers':[['1','2','3','4'],['5','6','7','8'],['10','20','30','40'],['11','12','13','14']],
'Score': ['1.1','2.2','3.3','4.4']})
desired output
Day numsearch Score
0 M 1 1.1
1 Tu 20 3.3
2 W 4 4.4
3 Th 99 "No score"
4 Fr 19 "No score"
5 Sa 6 2.2
6 Su 101 "No score"
I have written a for loop that works with the test data.
scores = []
for s,ns in enumerate(ppr_data['SN']):
match = ''
for k,q in enumerate(jcr_data['All_ISSNs']):
if ns in q:
scores.append(jcr_data['Journal Impact Factor'][k])
match = 1
else:
continue
if match == "":
scores.append('No score')
match = ""
df1['Score'] = np.array(scores)
In my small test, but above code works, but when working with larger data files, it is creating duplicates. So this clearly isn't the best way to do this.
I'm sure there's a more pandas-proper line of code that ends in .fillna("No score") .
I tried to use a loc statement, but I get hung up on searching the values of one dataframe in a column that contains lists.
Can anyone shed some light?

Answer 1

df2=df2.explode('Numbers')#Explode df2 on Numbers
d=dict(zip(df2.Numbers, df2.Score))#dict Numbers and Scores
df1['Score']=df1.numsearch.map(d).fillna('No Score')#Map dict to df1 filling NaN with No Score
Can shorten it as follows:
df2=df2.explode('Numbers')#Explode df2 on Numbers
df1['Score']=df1.numsearch.map(dict(zip(df2.Numbers, df2.Score))).fillna('No Score')
Day numsearch Score
0 M 1 1.1
1 Tu 20 3.3
2 W 14 4.4
3 Th 99 No Score
4 Fr 19 No Score
5 Sa 6 2.2
6 Su 101 No Score

Answer 2

You can try left join and fillna:
df1.merge(df2.explode('Numbers'),
left_on='numsearch',
right_on='Numbers', how='left')[['Day', 'numsearch', 'Score']].fillna("No score")
Output:
Day numsearch Score
0 M 1 1.1
1 Tu 20 3.3
2 W 14 4.4
3 Th 99 No score
4 Fr 19 No score
5 Sa 6 2.2
6 Su 101 No score