Intersection of list and dataframe, keeping duplicates of list but showing the values of a column in-CodePudding

Found this link and my work is somewhat similar.

Say I have:

x = ['the', 'the', 'and', 'a', 'apple', 'heart', 'heart']
y = {'words': ['the', 'belt', 'computer', 'heart','and'],'values':[3,2,1,1,4]}

Using the suggestion in the link above, I got this:

df = pd.DataFrame.from_dict(y)
items = set(df['words'])

found = [i for i in x if i in items] 
print(found)

The result is: ['the', 'the', 'and', 'heart', 'heart']

I want to be able to get the corresponding value of the word and I am stuck. The result I want is this:

[3,3,4,1,1]

Any thoughts on how to achieve this? Would greatly appreciate it.

CodePudding user response：

Not the most efficient one in my opinion, but this should do:

found = [df.loc[df['words'] == i, 'values'].iloc[0] for i in x if i in items]

CodePudding user response：

You don't need pandas. First rework your dictionary to have the words as keys, then use a comprehension:

y2 = dict(zip(*y.values()))
[y2[i] for i in x if i in y2]

Output: [3,3,4,1,1]

The (much less efficient) equivalent in pandas is:

s = df.set_index('words')['values']
pd.Series(x).map(s).dropna()

Output:

0    3.0
1    3.0
2    4.0
5    1.0
6    1.0
dtype: float64