CODEWITHSUNDEEP
pythonpandasvectorization
Abhishek Kulkarni
Abhishek Kulkarni

Reputation: 676

Vectorizing a function on a list of pandas dataframes

I read an excel file and save each tab as a pandas dataframe.

import pandas as pd
xla = pd.ExcelFile("file_name.xlsx")
kl=xla.sheet_names
hf_list=[]
for i in range(len(kl)):   
    hf_list.append(pd.read_excel(xla, i,index_col=0))

I intend to compute rank of each dataframe in the list so have written the following code.

def score_card(raw_list):    
    score_list=[]    
    for i in range(len(raw_list)):
        score_list.append(raw_list[i].rank(axis=1))        
    return score_list

score_list=score_card(hf_list)

I was wondering if there is a way to vectorize the code and avoid for loop(s) in the score_card function (and also reading the excel file). Thanks in advance for your time.

Upvotes: 2

Views: 183

Answers (1)

jezrael
jezrael

Reputation: 863291

If use parameter sheet_name = None in read_excel get orderdict of DataFrames for each sheetname:

dfs = pd.read_excel("file_name.xlsx", sheet_name = None, index_col=0)

Then use list comprehension:

score_list = [v.rank(axis=1) for k, v in dfs.items()]

Or create big DataFrame with concat:

df = pd.concat(dfs.values())

Upvotes: 2

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