CODEWITHSUNDEEP
pythonstringlistsublist
user5017783
user5017783

Reputation:

How can I make sublists from a list based on strings in python?

I have a list like this:

['<text id="32a45" language="ENG" date="2017-01-01" time="11:00" timezone="Eastern">',
'<text id="32a47" language="ENG" date="2017-01-05" time="1:00" timezone="Central">',
'<text id="32a48" language="ENG" date="2017-01-07" time="3:00" timezone="Pacific">']

From this I want to make sublists like:

id = ["32a45", "32a47", "32a48"]
date=["2017-01-01", "2017-01-05", "2017-01-07"]

How can I do that?

Thanks.

Edit: This was the original question It is a broken xml file and tags are messed up, hence I cannot use xmltree. So I am trying something else.

Upvotes: 2

Views: 143

Answers (7)

Anton vBR
Anton vBR

Reputation: 18906

Parsing with ET:

import xml.etree.ElementTree as ET
strings = ['<text id="32a45" language="ENG" date="2017-01-01" time="11:00" timezone="Eastern">',
'<text id="32a47" language="ENG" date="2017-01-05" time="1:00" timezone="Central">',
'<text id="32a48" language="ENG" date="2017-01-07" time="3:00" timezone="Pacific">']

id_ = []
date = []
for string in strings:
    tree = ET.fromstring(string+"</text>") #corrects wrong format
    id_.append(tree.get("id"))
    date.append(tree.get("date"))

print(id_) #  ['32a45', '32a47', '32a48']
print(date) # ['2017-01-01', '2017-01-05', '2017-01-07']

Update, full compact example: According to your original problem described here: How can I build an sqlite table from this xml/txt file using python?

import xml.etree.ElementTree as ET
import pandas as pd

strings = ['<text id="32a45" language="ENG" date="2017-01-01" time="11:00" timezone="Eastern">',
'<text id="32a47" language="ENG" date="2017-01-05" time="1:00" timezone="Central">',
'<text id="32a48" language="ENG" date="2017-01-07" time="3:00" timezone="Pacific">']

cols = ["id","language","date","time","timezone"]
data = [[ET.fromstring(string+"</text>").get(col) for col in cols] for string in strings]    
df = pd.DataFrame(data,columns=cols)

    id  language    date    time    timezone
0   32a45   ENG     2017-01-01  11:00   Eastern
1   32a47   ENG     2017-01-05  1:00    Central
2   32a48   ENG     2017-01-07  3:00    Pacific

Now you can use: df.to_sql()

https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_sql.html

Upvotes: 1

Rachit kapadia
Rachit kapadia

Reputation: 701

More easier way to understand with re module: Here is the code : 

l = ['<text id="32a45" language="ENG" date="2017-01-01" time="11:00" timezone="Eastern">', 
'<text id="32a47" language="ENG" date="2017-01-05" time="1:00" timezone="Central">',
 '<text id="32a48" language="ENG" date="2017-01-07" time="3:00" timezone="Pacific">']

import re
id =[]
dates= []
for i in l:
    id.append(re.search(r'id="(.+?)"',i, re.M|re.I).group(1))
    dates.append(re.search(r'date="(.+?)"',item, re.M|re.I).group(1))

Output:

print id     #id= ['32a45', '32a47', '32a48']
print dates  #dates= ['2017-01-07', '2017-01-07', '2017-01-07']

Upvotes: 0

AGN Gazer
AGN Gazer

Reputation: 8378

Not as elegant as @RomanPerekhrest solution using re but here it goes:

def extract(lst, kwd):
   out = []
   for t in lst:
       index1 = t.index(kwd) + len(kwd) + 1
       index2 = index1 + t[index1:].index('"') + 1
       index3 = index2 + t[index2:].index('"')
       out.append(t[index2:index3])
   return out

Then

>>> extract(lst, kwd='id')
['32a45', '32a47', '32a48']

Upvotes: 0

anteAdamovic
anteAdamovic

Reputation: 1468

Along with other answers who are better you can parse the data manually (more simple):

for line in lines:
    id = line[line.index('"')+1:]
    line = id
    line = id[line.index('"')+1:]
    id = id[:id.index('"')]
    print('id: ' + id)

You can then simply push it in the new list, repeat the same process for other values below simply change the variable name.

Upvotes: 0

Jake Conkerton-Darby
Jake Conkerton-Darby

Reputation: 1101

As your provided data appears to be broken/partial xml fragments I would personally try repairing the xml and using the xml.etree module to extract the data. However if you have correct xml that you have got your current list from, then it would be easier to use the xml.etree module on that data.

An example solution using xml.etree:

from xml.etree import ElementTree as ET

data = ['<text id="32a45" language="ENG" date="2017-01-01" time="11:00" timezone="Eastern">',
'<text id="32a47" language="ENG" date="2017-01-05" time="1:00" timezone="Central">',
'<text id="32a48" language="ENG" date="2017-01-07" time="3:00" timezone="Pacific">']

ids = []
dates = []
for element in data:
    #This wraps the element in a root tag and gives it a closing tag to
    #  repair the xml to a valid format.
    root = ET.fromstring('{}</text>'.format(element))

    #As we have formatted the xml ourselves we can guarantee that it's first
    #  child will always be the desired element.
    ids.append(root.attrib['id'])
    dates.append(root.attrib['date'])

print(ids)    # ['32a45', '32a47', '32a48']
print(dates)  # ['2017-01-01', '2017-01-05', '2017-01-07']

Upvotes: 0

RomanPerekhrest
RomanPerekhrest

Reputation: 92854

Simple solution using re.search() function:

import re

l = ['<text id="32a45" language="ENG" date="2017-01-01" time="11:00" timezone="Eastern">',
'<text id="32a47" language="ENG" date="2017-01-05" time="1:00" timezone="Central">',
'<text id="32a48" language="ENG" date="2017-01-07" time="3:00" timezone="Pacific">']

ids, dates = [], []
for i in l:
    ids.append(re.search(r'id="([^"]+)"', i).group(1))
    dates.append(re.search(r'date="([^"]+)"', i).group(1))

print(ids)    # ['32a45', '32a47', '32a48']
print(dates)  # ['2017-01-01', '2017-01-05', '2017-01-07']

Upvotes: 5

Andrey Lukyanenko
Andrey Lukyanenko

Reputation: 3851

id = [i.split(' ')[1].split('=')[1].strip('"') for i in list]
date = [i.split(' ')[3].split('=')[1].strip('"') for i in list]

But the file looks strange, if the original file is html or xml, there are better ways to get data.

Upvotes: 0

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