What kind of loop or function can be used to simplify this code?-CodePudding

Is there a loop or function that I can use in Python to simplify down this code, so that I can go through an entire list and return the result of each iteration? I need to apply the value of the row index to iloc and as a function parameter.

I've tried while loops, but I get <function __main__.()> in return when I put it in a function.

IndexList = [0,1,2,3,4,5,6,...,99]

IndexPosition = 0
row_index = IndexList.index[IndexPosition]
Result = dfColumn1.iloc[row_index] / dfFunction(row_index) 
Result 
#Output

IndexPosition = 1
row_index = IndexList.index[IndexPosition]
Result = dfColumn1.iloc[row_index] / dfFunction(row_index) 
Result 
#Output

IndexPosition = 2
row_index = IndexList.index[IndexPosition]
Result = dfColumn1.iloc[row_index] / dfFunction(row_index) 
Result 
#Output

etc

Ideally, I'd like it so the output is:

#Output of function from Index Position 1
#Output of function from Index Position 2
#Output of function from Index Position 3
#Output of function from Index Position 4

CodePudding user response：

I think you can use a for(each) loop with index using the built-in function enumerate():

for value, index in enumerate(IndexList):
    print(value, index)

CodePudding user response：

You might want to take a few steps back from the columns and indexes you extracted. Pandas dataframes offer a lot of direct ways to iterate over the columns or cells themselves.

import pandas as pd

df = pd.DataFrame({'x': {0: 1, 1: 200, 2: 4, 3: 5, 4: 6}, 
                     'y': {0: 4, 1: 5, 2: 10, 3: 24, 4: 4},
                     'z': {0: 1, 1: 2, 2: 3, 3: 4, 4: 5}
              })
results = []
for idx, x in enumerate(df.iloc[:, 1]):
    results.append(df.iloc[idx] / dfFunction(x))

for res in results:
    print(res)