Split List of values to dataframe in Python

Question

So I was trying to split a list of values into dataframe in Python.

Here is a sample example of my list

    ini_string1 = "Time=2014-11-07 00:00:00,strangeness=0.0001,p-value=0.19,deviation=0.78,D_Range=low'"
    templist = []  
    for i in range(5):
        templist.append({ini_string1})

Now I was trying to create a dataframe with Time, Strangeness, P-Values, Deviation, D_Range as variables.

I was able to get a data frame when I have only one sigle value of ini_string but counld not make it when I have list of values.

Below is a sample code I tried with single value ini_string

lst_dict = []

cols = ['Time','Strangeness', 'P-Values', 'Deviation', 'Is_Deviation']
# Initialising string 

for i in range(5):
    ini_string1 = "Time=2014-11-07 00:00:00,strangeness=0.0001,p-value=0.19,deviation=0.78,D_Range=low'"

tempstr = ini_string1 
res = dict(item.split("=") for item in tempstr.split(","))
lst_dict.append({'Time': res['Time'],
                 'Strangeness': res['strangeness'],
                 'P-Values': res['p-value'],
                 'Deviation': res['deviation'],
                 'Is_Deviation': res['D_Range']})

print(lst_dict)

strdf = pd.DataFrame(lst_dict, columns=cols)

I could not figureout the implementation for list of values

Shiva · Accepted Answer · 2019-09-07 11:49:21Z

3

The below code will do the job.

from collections import defaultdict
import pandas as pd

ini_string1 = "Time=2014-11-07 00:00:00,strangeness=0.0001,p-value=0.19,deviation=0.78,D_Range='low'"
ini_string2 = "Time=2015-12-07 00:00:00,strangeness=0.0005,p-value=0.31,deviation=0.01,D_Range='high'"

ini_strings = [ini_string1, ini_string2] 

dd = defaultdict(list)
for ini_str in ini_strings:
    for key_val in ini_str.split(','):
        k, v = key_val.split('=')
        dd[k].append(v)

df = pd.DataFrame(dd)

Read more about defaultdict - How does collections.defaultdict work?
Python has other interesting data structures - https://docs.python.org/2/library/collections.html

edited Sep 7, 2019 at 11:49

answered Sep 7, 2019 at 11:42

Shiva

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