CODEWITHSUNDEEP
pythonpandas
AGarofoli
AGarofoli

Reputation: 157

Parsing pandas tables

I have a (probably dumb) issue with pandas' tables. Let's say I have a table with, among the others, a column named 'lett', that includes a single letter for each row, and a column named 'num', with a number. I also have the following 2 lists

letter=["A", "B", "C"]

number=[[1, 2], [3, 4], [5, 6]]

Now, I want to extract all the rows with A in the letter column and 1 or 2 in the number column, B with 3 or 4 and C with 5 or 6.

My idea was to run 

table['num'].isin(number[letter.index(table['lett'])])

But I get the following issue: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). (maybe because table['lett'] does not refer to the specific row, but to the whole possible values included in the 'lett' column?). What am I supposed to do? Thanks in advance

Upvotes: 0

Views: 46

Answers (1)

BENY
BENY

Reputation: 323226

First make your two lists to list of tuple , then make your columns number and letter to a tuple as well , then we can using isin 

tup=[(x,z)for x , y in zip(letter,number) for z in y ]
yourdf=df[df[['letter','Number']].apply(tuple,axis = 1).isin(tup)]

Or using merge 

pd.DataFrame(tup,columns=['letter','number']).merge(df,how='left')

Upvotes: 2

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