Define function to convert string to integer in Python

Question

This is likely a very simple question but I would appreciate help!

As part of a larger script, I have a dataframe (imported from a csv file) with two columns, 'file_name' and 'value'. I have a short example below:

            file_name  value
0  201623800811s.fits   True
1  201623802491s.fits   True
2  201623802451s.fits  False

I would like to define a function that reads the values within column 'value', and returns 0 for 'False' and 1 for 'True'. I would then like to append the results to a third column in the dataframe, and finally export the updated dataframe to the csv.

I have defined a function that appears to me to work. However, when I run the script it does not execute and I receive the message:

<function convert_string at 0x000000000DE35588>

In the console. My function is below. Any help or advice will be welcomed.

def convert_string(explosions):
    for i in range(0,len(explosions)):
        if i == 'True' :
            return 1
        elif i == 'False' :
            return 0
        else:
            return 2

print convert_string

You never call your function.

Jörg W Mittag
– Jörg W Mittag

2017-06-29 12:09:49 +00:00
Commented Jun 29, 2017 at 12:09 — Jörg W Mittag
– Jörg W Mittag, Commented Jun 29, 2017 at 12:09

DeepSpace · Accepted Answer · 2017-06-29 12:18:06Z

1

If you are using an explicit for loop when working with a dataframe, you are most probably "doing it wrong". Also, what is the point of having a for loop if you return on the very first iteration?

Consider these:

import numpy as np

df['third_column'] = np.where(df['value'], 1, 0)

If you insist on defining a function:

def foo(x):
    return int(x)

df['third_column'] = df['value'].apply(foo)

or simply

df['third_column'] = df['value'].apply(lambda x: int(x))

Full example:

import pandas as pd
import numpy as np

df = pd.DataFrame({'value': [True, False]})
print(df)

#     value
#  0   True
#  1  False

df['third_column'] = np.where(df['value'], 1, 0) 
print(df)

#     value  third_column
#  0   True             1
#  1  False             0

edited Jun 29, 2017 at 12:18

answered Jun 29, 2017 at 12:12

DeepSpace

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1 Comment

ailsa_naismith Over a year ago

Thank you, this is a useful set of alternatives written much more elegantly than my own code. When you say that explicit use of a for loop with a dataframe is "doing it wrong", is that because your dataframe already defines the data you wish to use?

Bovarysme · Accepted Answer · 2017-06-29 12:12:57Z

0

You're not calling the function. Your print statement should be: print convert_string(<value>), where <value> is an integer.

answered Jun 29, 2017 at 12:12

Bovarysme

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