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I have the Python code below and I would like the output to be a string: "P-1888" discarding all numbers after the 2nd "-" and removing the leading 0's after the 1st "-".
So far all I have been able to do in the following code is to remove the trailing 0's:
import re
docket_no = "P-01888-000"
doc_no_rgx1 = re.compile(r"^([^\-]+)\-(0+(.+))\-0[\d]+$")
massaged_dn1 = doc_no_rgx1.sub(r"\1-\2", docket_no)
print(massaged_dn1)
You can use the split() method to split the string on the "-" character and then use the join() method to join the first and second elements of the resulting list with a "-" character. Additionally, you can use the lstrip() method to remove the leading 0's after the 1st "-". Try this.
docket_no = "P-01888-000"
docket_no_list = docket_no.split("-")
docket_no_list[1] = docket_no_list[1].lstrip("0")
massaged_dn1 = "-".join(docket_no_list[:2])
print(massaged_dn1)
First way is to use capturing groups. You have already defined three of them using brackets. In your example the first capturing group will get "P", and the third capturing group will get numbers without leading zeros. You can get captured data by using re.match:
match = doc_no_rgx1.match(docket_no)
print(f'{match.group(1)}-{match.group(3)}') # Outputs 'P-1888'
Second way is to not use regex for such a simple task. You could split your string and reassemble it like this:
parts = docket_no.split('-')
print(f'{parts[0]}-{parts[1].lstrip("0")}')
It seems like a sledgehammer/nut situation but of you do want to use re then you could use:
doc_no_rgx1 = ''.join(re.findall('([A-Z]-)0+(\d+)-', docket_no)[0])
I don't think I'd use a regular expression for this purpose. Your usecase can be handled by standard string manipulation so using a regular expression would be overkill. Instead, consider doing this:
docket_nos = "P-01888-000".split('-')[:-1]
docket_nos[1] = docket_nos[1].lstrip('0')
docket_no = '-'.join(docket_nos)
print(docket_no) # P-1888
This might seem a little bit verbose but it does exactly what you're looking for. The first line splits docket_no by '-' characters, producing substrings P, 01888 and 000; and then discards the last substring. The second line strips leading zeros from the second substring. And the third line joins all these back together using '-' characters, producing your desired result of P-1888.
Functionally this is no different than other answers suggesting that you split on '-' and lstrip the zero(s), but personally I find my code more readable when I use multiple assignment to clarify intent vs. using indexes:
def convert_docket_no(docket_no):
letter, number, *_ = docket_no.split('-')
return f'{letter}-{number.lstrip("0")}'
_ is used here for a "throwaway" variable, and the * makes it accept all elements of the split list past the first two.
I have a data frame where the values I want are in the same cell like this - words and all:
depth: 3230 m - 3750 m
I'm trying to write a regex to return the first number and then the second into a new data frame.
so far, I can get the values with this:
top_depthdf=df[0].str.extract(r'depth:\s(\d+(?:\.\d+)?)', flags=re.I).astype(float)
base_depthdf=df[0].str.extract(r'-\s(\d+(?:\.\d+)?)', flags=re.I).astype(float)
where I am having an issue is that these patterns are not unique in this data, especially the base depth one. Other numbers have a similar pattern and my script is returning them instead of the base depth if they occur before the depth row. I was wondering if there is a way to write the base_depthdf in such a way that it looks for the 'depth:' part first and then looks for that pattern?
You can capture these numbers with two named capturing groups into two columns at once:
df_depth = df[0].str.extract(r'depth:\s*(?P<top_depth>\d+(?:\.\d+)?)(?:\s*\w+)?\s*-\s*(?P<base_depth>\d+(?:\.\d+)?)')
See the regex demo. The (?P<top_depth>...) and (?P<base_depth>...) capture the details into separate columns.
I used (?:\s*\w+)?\s* to match a single optional word between the two patterns, but you may just use .*? if you are not sure what can appear between the two:
df_depth = df[0].str.extract(r'depth:\s*(?P<top_depth>\d+(?:\.\d+)?).*?-\s*(?P<base_depth>\d+(?:\.\d+)?)')
Pandas test:
df = pd.DataFrame({'c':['depth: 3230 m - 3750 m']})
df_depth = df['c'].str.extract(r'depth:\s*(?P<top_depth>\d+(?:\.\d+)?)(?:\s*\w+)?\s*-\s*(?P<base_depth>\d+(?:\.\d+)?)')
print(df_depth.to_string())
Output:
top_depth base_depth
0 3230 3750
Lets say I have Strings like:
"H39_M1", "H3_M15", "H3M19", "H3M11", "D363_H3", "D_128_H17_M50"
How can I split them every single one into a list of substrings?
like this:
["H39", "M1"], "[H3, "Min15"], ["H3","M19"], ["H3","M11"], ["D363","H3"], ["D128","H17","M50"]
and afterwards: switch places of alphanumeric-group and numeric group,
like this:
["39H", "1M"], "[3H, "15Min"], ["3H","19M"], ["3H","11M"], ["363D","3H"],["128D","17H","50M"]
length of numbers-group and of alphanumeric group varys as you can see.
also "_" underscores can divide them.
I might suggest using re.findall here with re.sub:
inp = "H3M19"
inp = re.sub(r'([A-Z]+)([0-9]+)', r'\2\1', inp)
parts = re.findall(r'[0-9]+[A-Z]+', inp)
print(parts)
This prints:
['3H', '19M']
The first re.sub step converts H3M19 into 3H19M, by capturing the letter and numeric pairs and then swapping them. Then, we use re.findall to find all number/letter pairs in the swapped input.
I receive an input string having values expressed in two possible formats. E.g.:
#short format
data = '"interval":19'
>>> "interval":19
#extended format
data = '"interval":{"t0":19,"tf":19}'
>>> "interval":{"t0":19,"tf":19}
I would like to check whether a short format is used and, in case, make it extended.
Considering that the string could be composed of multiple values, i.e.
data = '"interval":19,"interval2":{"t0":10,"tf":15}'
>>> "interval":19,"interval2":{"t0":10,"tf":15}
I cannot just say:
if ":{" not in data:
#then short format is used
I would like to code something like:
if ":$(a general int/float/double number)" in data:
#extract the number
#replace ":{number}" with the extended format
I know how to code the replacing part.
I need help for implementing if condition: in my mind, I model it like a variable substring, in which the variable part is the number inside it, while the rigid format is the $(value name) + ":" part.
"some_value":19
^ ^
rigid format variable part
EDIT - WHY NOT PARSE IT?
I know the string is "JSON-friendly" and I can convert it into a dictionary, easily accessing then the values.
Indeed, I already have this solution in my code. But I don't like it since the input string could be multilevel and I need to iterate on the leaf values of the resulting dictionary, independently from the dictionary levels. The latter is not a simple thing to do.
So I was wondering whether a way to act directly on the string exists.
If you replace all keys, except t0, tf, followed by numbers, it should work.
I show you an example on a multilevel string, probably to be put in a better shape:
import re
s = '"interval": 19,"t0interval2":{"t0":10,"tf":15},{"deeper": {"other_interval":23}}'
gex = '("(?!(t0|tf)")\w+":)\s*(\d+)'
new_s = re.sub(gex, r'\1 {"t0": \3, "tf": \3}', s)
print(new_s)
>>> print(new_s)
"interval": {"t0": 19, "tf": 19},"t0interval2":{"t0":10,"tf":15},{"deeper": {"other_interval": {"t0": 23, "tf": 23}}}
You could use a regular expression. ("interval":)(\d+) will look for the string '"interval":' followed by any number of digits.
Let's test this
data = '"interval":19,"interval2":{"t0":10,"tf":15},"interval":25'
result = re.sub(r'("interval":)(\d+)', r'xxx', data)
print(result)
# -> xxx,"interval2":{"t0":10,"tf":15},xxx
We see that we found the correct places. Now we're going to create your target format. Here the matched groups come in handy. In the regular expression ("interval":) is group 1, (\d+) is group 2.
Now we use the content of those groups to create your wanted result.
data = '"interval":19,"interval2":{"t0":10,"tf":15},"interval":25'
result = re.sub(r'("interval":)(\d+)', r'\1{"t0":\2,"tf":\2}', data)
print(result)
# -> "interval":{"t0":19,"tf":19},"interval2":{"t0":10,"tf":15},"interval":{"t0":25,"tf":25}
If there are floating point values involved you'll have to change (\d+) to ([.\d]+).
If you want any Unicode standard word characters and not only interval you can use the special sequence \w and because it could be multiple characters the expression will be \w+.
data = '"interval":19,"interval2":{"t0":10,"tf":15},"Monty":25.4'
result = re.sub(r'("\w+":)([.\d]+)', r'\1{"t0":\2,"tf":\2}', data)
print(result)
# -> "interval":{"t0":19,"tf":19},"interval2":{"t0":{"t0":10,"tf":10},"tf":{"t0":15,"tf":15}},"Monty":{"t0":25.4,"tf":25.4}
Dang! Yes, we found "Monty" but now the values from the second part are found too. We'll have to fix this somehow. Let's see. We don't want ("\w+") if it's preceded by { so were going to use a negative lookbehind assertion: (?<!{)("\w+"). And after the number part (\d+) we don't want a } or an other digit so we're using a negative lookahead assertion here: ([.\d]+)(?!})(?!\d).
data = '"interval":19,"interval2":{"t0":10,"tf":15},"Monty":25.4'
result = re.sub(r'(?<!{)("\w+":)([.\d]+)(?!})(?!\d)', r'\1{"t0":\2,"tf":\2}', data)
print(result)
# -> "interval":{"t0":19,"tf":19},"interval2":{"t0":10,"tf":15},"Monty":{"t0":25.4,"tf":25.4}
Hooray, it works!
Regular expressions are powerful and fun, but if you start to add more constraints this might become unmanageable.
To look through data, I am using regular expressions. One of my regular expressions is (they are dynamic and change based on what the computer needs to look for --- using them to search through data for a game AI):
O,2,([0-9],?){0,},X
After the 2, there can (and most likely will) be other numbers, each followed by a comma.
To my understanding, this will match:
O,2,(any amount of numbers - can be 0 in total, each followed by a comma),X
This is fine, and works (in RegExr) for:
O,4,1,8,6,7,9,5,3,X
X,6,3,7,5,9,4,1,8,2,T
O,2,9,6,7,11,8,X # matches this
O,4,6,9,3,1,7,5,O
X,6,9,3,5,1,7,4,8,O
X,3,2,7,1,9,4,6,X
X,9,2,6,8,5,3,1,X
My issue is that I need to match all the numbers after the original, provided number. So, I want to match (in the example) 9,6,7,11,8.
However, implementing this in Python:
import re
pattern = re.compile("O,2,([0-9],?){0,},X")
matches = pattern.findall(s) # s is the above string
matches is ['8'], the last number, but I need to match all of the numbers after the given (so '9,6,7,11,8').
Note: I need to use pattern.findall because thee will be more than one match (I shortened my list of strings, but there are actually around 20 thousand strings), and I need to find the shortest one (as this would be the shortest way for the AI to win).
Is there a way to match the entire string (or just the last numbers after those I provided)?
Thanks in advance!
Use this:
O,2,((?:[0-9],?){0,}),X
See it in action:http://regex101.com/r/cV9wS1
import re
s = '''O,4,1,8,6,7,9,5,3,X
X,6,3,7,5,9,4,1,8,2,T
O,2,9,6,7,11,8,X
O,4,6,9,3,1,7,5,O
X,6,9,3,5,1,7,4,8,O
X,3,2,7,1,9,4,6,X
X,9,2,6,8,5,3,1,X'''
pattern = re.compile("O,2,((?:[0-9],?){0,}),X")
matches = pattern.findall(s) # s is the above string
print matches
Outputs:
['9,6,7,11,8']
Explained:
By wrapping the entire value capture between 2, and ,X in (), you end up capturing that as well. I then used the (?: ) to ignore the inner captured set.
you don't have to use regex
split the string to array
check item 0 == 0 , item 1==2
check last item == X
check item[2:-2] each one of them is a number (is_digit)
that's all