How to create separate data frames based on row numbers in a loop

Question

I am reading in data from an excel file. And currently I am breaking down it several different DFs based on the row numbers. What I want to do is create a loop which will iterate over the imputed row numbers and create different Dfs with the appropriate suffixes. Currently I am creating separate Dfs by passing in row numbers in each line.

NHE_17= NHE_data.parse('NHE17') 
#Slice DataFrame for only Total National Health Expenditure data, from 
row 0 to 37(Population): total_nhe
total_nhe = NHE_17.iloc[0:37]
print(total_nhe.iloc[0,-1])
#Slice DataFrame for only Health Consumption Expenditures, from row 38 to 
70(Total CMS Programs (Medicaid, CHIP and Medicare): total_hce
total_hce = NHE_17.iloc[38:70]

I want to be able call the function with the row numbers and suffix to create the specific DF.

Tiblit · Accepted Answer · 2019-02-08 15:47:40Z

1

that function would look like:

   def row_slicer(slice_tuple):

      #This will slice the NHE_17 according to slice_parameters parameters
      # Input slice_tuple = [x1,x1 

      df_temp = NHE_17.iloc[slice_tuple[0]:slice_tuple[1]]
      return df_temp

   dict_dataframes = {}

   #assuming this is a dictionary, else you can  zip lists with pandas columns
   name_list_row = [['total_nhe',[0,37]],['total_hce',[38,70]]...]

   for name,slice_tuple in name_list_row:
      df = row_slicer(slice_tuple)
      dict_dataframes[name] = df

Hope this helps!

answered Feb 8, 2019 at 15:47

Tiblit

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