<jupyter_start><jupyter_text><jupyter_code>#name = <NAME>
#a, c

name = "<NAME>"
first, *last = name.split()
print("First = {first}".format(first=first))
#First = John
print("Last = {last}".format(last=" ".join(last)))
#Last = <NAME>
name = "<NAME>"
first, *last = name.split()
print("First = {first}".format(first=first))
#First = John
print("Last = {last}".format(last=" ".join(last)))
#Last = Schmidt
name = "<NAME>"
first, middle, *last = name.split()
print("First = {first}".format(first=first))
#First = John
print("Middle = {middle}".format(middle=middle))
#Middle = Jacob
print("Last = {last}".format(last=" ".join(last)))
#Last = <NAME>
address = "<NAME>"
first, middle, *last = address.split()

print("First = {first}".format(first=first))

#First = John
print("Middle = {middle}".format(middle=middle))
#Middle = Jacob
print("Last = {last}".format(last=" ".join(last)))
#Last = Jingleheimer Schmidt
full_name = "<NAME>"
address = "405 Rock Plant Lane, Fort Worth, Texas, 76144, <EMAIL>, (817)-323-8783"
first, MiddleInitial, last = full_name.split(" ", 3)
street, street1, street2, street3, street4 = address.split(" ", 4)
#street5 = address.split(" ", 4)
#street, city, state, zipcode = address.split(" ", 4)
print(first+" "+MiddleInitial+" "+last)

print(street+ " "+street1+" "+street2+" "+street3)
print(street4)
# " "+street5 )
pip install nameparser
from nameparser import HumanName

# Here's a full name, with a nickname
full_name = 'Mr. Mathew "<NAME>" Oloo'

# Extract values
parsed_name = HumanName(full_name)

# Get just the first and last name
f_name = parsed_name.first
l_name = parsed_name.last

print(f_name, l_name)
# <NAME>

# ------------------------------

# If you want to see everything:
parsed_name.as_dict()
{'title': 'Mr.',
 'first': 'Mathew',
 'middle': '',
 'last': 'Oloo',
 'suffix': '',
 'nickname': 'The Boss'}
txt = "hello, my name is Peter, I am 26 years old"

x = txt.split(", ")

print(x)
txt = "413 Rockanne Blvd, Fort Worth, Texas, 76151, <EMAIL>, 814-325-2254"

x = txt.split(", ")#,"/n")

print(x)
txt = "413 Rockanne Blvd, Fort Worth, Texas, 76151, <EMAIL>, 814-325-2254"

a, b, c, d, e, f= txt.split(", ")#,"/n")

print(a)
print(b+"," " "+c+"," " "+d+".")
print(e)
print(f)
x = 'Exodus, Corinthians, Thesalonians'
a, b, c = x.split(",")
print(a)
print(b)
print(c)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.22279129321382843, 'fraction_numerical': 0.02987622705932565, 'mean_word_length': 5.025706940874036, 'pattern_counts': {'":': 0, '<': 18, '<?xml version=': 0, '>': 18, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '509477', 'license': 'MIT', 'n_tokens_mistral': 936, 'n_tokens_neox': 870, 'n_words': 232, 'path': 'Strings_galore.ipynb', 'repo_name': 'gndede/python', 'size': '2510'}