python assign variables from values in a list

Question

I have a csv file I'm importing as a list

[["df['EPS Rating']>=97"],
 ["df['RS Rating']>=97"],
 ["df['Ind Group RS']<=9"],
 ["df['SMR Rating']<=2"],
 ["df['AD Rating']<=9"],
 ["df['Comp Rating']>=85"],
 ["df['Current Price']>=15"]]

I would like to assign each of these to variables c1 to c7 like this

c1 = df['EPS Rating']>=97
c2 = df['RS Rating']>=97
c3 = df['Ind Group RS']<=9
c4 = df['SMR Rating']<=2
c5 = df['AD Rating']<=9
c6 = df['Comp Rating']>=85
c7 = df['Current Price']>=15

This is so I can use this excellent solution I found by Gecko here also shown below. While this solution is great for readability in my case it ends up being huge as I have more than 30 of these filters and many with more than 20 conditions. How can I assign strings in a list to variables?

something like this maybe?

For i to end_of_list:
    c[i] = [i].value

I hope that explains what I'm trying to do. I'm new to python so I'm still a bit lost. I'm not attached to this idea so if anyone has a better solution I'd love to know it. Thanks

Geckos Original Solution:

import numpy as np
import functools
def conjunction(*conditions):
    return functools.reduce(np.logical_and, conditions)

c_1 = data.col1 == True
c_2 = data.col2 < 64
c_3 = data.col3 != 4

data_filtered = data[conjunction(c1,c2,c3)]

so that they can be used with the original solution by Gecko — wraith
– wraith, Commented Feb 25, 2020 at 19:38
The problem I'm seeing here is that in your situation, you're importing a list of dataframe expressions as strings, and in the solution you posted, the conjuction function is being applied to the evaluation of those expressions. In your situation, how is the actual DataFrame object computed? — Jon Behnken
– Jon Behnken, Commented Feb 25, 2020 at 19:49

Jon Behnken · Accepted Answer · 2020-02-25 20:25:35Z

1

Try this:

strings = [["df['EPS Rating']>=97"],
 ["df['RS Rating']>=97"],
 ["df['Ind Group RS']<=9"],
 ["df['SMR Rating']<=2"],
 ["df['AD Rating']<=9"],
 ["df['Comp Rating']>=85"],
 ["df['Current Price']>=15"]]

filters = []
for i in strings:
    filters.append(eval(i[0]))

data_filtered = df[conjunction(*filters)]

You can pass that conjunction function a list as long as you unpack it in place, as done here.

Note: this assumes you have the actual DataFrame object df initialized somewhere in your code prior to running.

Edit: FWIW, this solution would do exactly what you asked for, creating dynamically assigned variables that hold the evaluation of the expression in the string:

for i in range(len(g)):
    x = 'c_{}'.format(i)
    exec('{} = {}'.format(x,g[i][0].strip("\"")))

but instantiating variables this way (with no explicit assignment statement) is generally terrible practice (see link for further information).

edited Feb 25, 2020 at 20:25

answered Feb 25, 2020 at 20:18

Jon Behnken

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1 Comment

wraith Over a year ago

This first solution is exactly what I didn't even know I was looking for. It works great. Also thanks for including the second and the link to why that is not a good idea. You're help is greatly appricated.

Umar.H · Accepted Answer · 2020-02-25 19:58:14Z

1

IIUC, you can just hold each item in a dictionary.

filter_dict = {}
counter = 1
for item in your_list:
    for i in item:
        filter_dict[f'C{counter}'] = i 
        counter += 1

print(filter_dict)

{'C1': "df['EPS Rating']>=97",
 'C2': "df['RS Rating']>=97",
 'C3': "df['Ind Group RS']<=9",
 'C4': "df['SMR Rating']<=2",
 'C5': "df['AD Rating']<=9",
 'C6': "df['Comp Rating']>=85",
 'C7': "df['Current Price']>=15"}

this gives you a string version of your object, you'll have to use eval to use it in your function.

import numpy as np
import functools

def conjunction(*conditions):
    return functools.reduce(np.logical_and, conditions)



df[conjunction([eval(x) for x in filter_dict.values()])

Note, the eval will cause an error if the object doesn't exist in your dataframe.

answered Feb 25, 2020 at 19:58

Umar.H

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1 Comment

wraith Over a year ago

While I wasn't able to get this to work it actually gave me an idea to fix something else I'm working on, so thank you.

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