How to iterate over multiple function arguments?

Question

I'm trying to use either locals() or *args to iterate over multiple function arguments. However, I am defining the function arguments as columns from a dataframe. How do I edit the following to have the float_format function iterate over a variable number of arguments?

#! /usr/bin/env python3

import pandas as pd

def float_format(a, b, c, d, e, f): #Change to single *args function argument?
        for x in range(len(data[a])):
                data[a][x] = data[a][x].replace(' Mbps', '')
        for x in range(len(data[b])):
                data[b][x] = data[b][x].replace(' Mbps', '')
        for x in range(len(data[c])):
                data[c][x] = data[c][x].replace(' Mbps', '')                
        for x in range(len(data[d])):
                data[d][x] = data[d][x].replace(' Mbps', '')
        for x in range(len(data[e])):
                data[e][x] = data[e][x].replace(' Mbps', '')
        for x in range(len(data[f])):
                data[f][x] = data[f][x].replace(' Mbps', '')

file = r'Original_File.xls'
data = pd.read_excel(file, header=[2])

float_format('Average Receive bps',
               'Peak Receive bps',
               'Received Bandwidth',
               'Average Transmit bps',
               'Peak Transmit bps',
               'Transmit Bandwidth')

data.to_excel('results.xlsx', 'w+')

So if I try

def float_format(*iterate):
        for arg in iterate:
            for x in range(len(data[iterate])):
                    data[iterate][x] = data[iterate][x].replace(' Mbps', '')

I'm getting traceback errors over the way the function runs.

example df

>>> data
            Display Name Interface Name  ... Peak Transmit bps Transmit Bandwidth
0       1951 - LAB - FW1          port1  ...         0.56 Mbps         10.00 Mbps
1       1951 - LAB - FW1          port1  ...         0.37 Mbps         10.00 Mbps
2       1951 - LAB - FW1          port1  ...         0.34 Mbps         10.00 Mbps
3       1951 - LAB - FW1          port1  ...         0.36 Mbps         10.00 Mbps
4       1951 - LAB - FW1          port1  ...         0.83 Mbps         10.00 Mbps
5       1951 - LAB - FW1          port1  ...         0.55 Mbps         10.00 Mbps
6       1951 - LAB - FW1          port1  ...         0.27 Mbps         10.00 Mbps
7       1951 - LAB - FW1          port1  ...         0.41 Mbps         10.00 Mbps
8       1951 - LAB - FW1          port2  ...         0.00 Mbps       1000.00 Mbps
9       1951 - LAB - FW1          port2  ...         0.00 Mbps       1000.00 Mbps
10      1951 - LAB - FW1          port2  ...         0.00 Mbps       1000.00 Mbps
11      1951 - LAB - FW1          port2  ...         0.00 Mbps       1000.00 Mbps
12      1951 - LAB - FW1          port2  ...         0.00 Mbps       1000.00 Mbps
13      1951 - LAB - FW1          port2  ...         0.00 Mbps       1000.00 Mbps
14      1951 - LAB - FW1          port2  ...         0.19 Mbps       1000.00 Mbps
15      1951 - LAB - FW1          port2  ...         0.31 Mbps       1000.00 Mbps

You can make a list and iterate over for i in [a,b,c,d,e,f]. Or if you want a variadic function, indeed use *args. — willeM_ Van Onsem
– willeM_ Van Onsem, Commented Feb 4, 2020 at 18:54
Can you explain what the function is meant to do in the first place? It doesn't look very idiomatic. — AMC
– AMC, Commented Feb 4, 2020 at 19:40
@cgarrido What value? That sounds quite simple, why does the function look so complex? Can you take a step back, and provide some more context for the operation? — AMC
– AMC, Commented Feb 4, 2020 at 20:16

Greg · Accepted Answer · 2020-02-04 18:57:52Z

4

How about the following?

def test(*argv):
    for arg in argv:
            print(arg)

test('hello', 'world')
# hello
# world

answered Feb 4, 2020 at 18:57

Greg

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2 Comments

cgarrido Over a year ago

I tried something similar in my edit but I get a pretty lengthy traceback when trying to use *args.

Greg Over a year ago

Can you please post the traceback?

AMC · Accepted Answer · 2020-02-04 21:00:51Z

There's no need to use *args or anything like that here, we can take advantage of the operations provided by Pandas.

Setup code

import numpy as np
import pandas as pd

df_1 = pd.DataFrame(data={'col_1': np.random.randint(0, 10, 10),
                          'col_2': np.random.randint(0, 50, 10),
                          'col_3': np.random.randint(0, 5, 10)})

df_1[['col_1', 'col_3']] = df_1[['col_1', 'col_3']].astype(str) + ' Mbps'

print(df_1)
print(df_1.dtypes)

Output:

    col_1  col_2   col_3
0  1 Mbps     45  0 Mbps
1  2 Mbps     34  1 Mbps
2  6 Mbps     46  2 Mbps
3  7 Mbps      2  1 Mbps
4  6 Mbps     36  0 Mbps
5  9 Mbps     36  3 Mbps
6  4 Mbps     39  1 Mbps
7  4 Mbps     26  1 Mbps
8  1 Mbps     10  1 Mbps
9  6 Mbps      1  1 Mbps
col_1    object
col_2     int64
col_3    object
dtype: object

Method 1: `Series.str.extract()`

Using a loop

cols_to_change = ['col_1', 'col_3']

for col_name in cols_to_change:
    df_1[col_name] = df_1[col_name].str.extract(r"(\d+) Mbps", expand=False).astype(int)

Using DataFrame.apply()

cols_to_change = ['col_1', 'col_3']

df_1[cols_to_change] = df_1[cols_to_change].apply(lambda col: col.str.extract(r"(\d+) Mbps", expand=False)).astype(int)

Method 2: `Series.str.slice()`

Using a loop

cols_to_change = ['col_1', 'col_3']

for col_name in cols_to_change:
    df_1[col_name] = df_1[col_name].str.slice(stop=-5).astype(int)

Using DataFrame.apply()

cols_to_change = ['col_1', 'col_3']

df_1[cols_to_change] = df_1[cols_to_change].apply(lambda col: col.str.slice(stop=-5)).astype(int)

Result

DataFrame contents:

   col_1  col_2  col_3
0      9     40      3
1      4      8      3
2      6     49      4
3      4     38      4
4      6     25      4
5      3      8      3
6      3     27      3
7      0     45      1
8      7     24      4
9      3     29      2

dtypes:

col_1    int64
col_2    int64
col_3    int64
dtype: object

Let me know if you have any questions :)

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How to iterate over multiple function arguments?

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Setup code

Method 1: `Series.str.extract()`

Method 2: `Series.str.slice()`

Result

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Collectives™ on Stack Overflow

2 Answers 2

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Setup code

Method 1: Series.str.extract()

Method 2: Series.str.slice()

Result

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Method 1: `Series.str.extract()`

Method 2: `Series.str.slice()`