I would like to use the .replace function to replace multiple strings.
I currently have
string.replace("condition1", "")
but would like to have something like
string.replace("condition1", "").replace("condition2", "text")
although that does not feel like good syntax
what is the proper way to do this? kind of like how in grep/regex you can do \1 and \2 to replace fields to certain search strings
Here is a short example that should do the trick with regular expressions:
import re
rep = {"condition1": "", "condition2": "text"} # define desired replacements here
# use these three lines to do the replacement
rep = dict((re.escape(k), v) for k, v in rep.iteritems())
#Python 3 renamed dict.iteritems to dict.items so use rep.items() for latest versions
pattern = re.compile("|".join(rep.keys()))
text = pattern.sub(lambda m: rep[re.escape(m.group(0))], text)
For example:
>>> pattern.sub(lambda m: rep[re.escape(m.group(0))], "(condition1) and --condition2--")
'() and --text--'
You could just make a nice little looping function.
def replace_all(text, dic):
for i, j in dic.iteritems():
text = text.replace(i, j)
return text
where text is the complete string and dic is a dictionary — each definition is a string that will replace a match to the term.
Note: in Python 3, iteritems() has been replaced with items()
Careful: Python dictionaries don't have a reliable order for iteration. This solution only solves your problem if:
order of replacements is irrelevant
it's ok for a replacement to change the results of previous replacements
Update: The above statement related to ordering of insertion does not apply to Python versions greater than or equal to 3.6, as standard dicts were changed to use insertion ordering for iteration.
For instance:
d = { "cat": "dog", "dog": "pig"}
my_sentence = "This is my cat and this is my dog."
replace_all(my_sentence, d)
print(my_sentence)
Possible output #1:
"This is my pig and this is my pig."
Possible output #2
"This is my dog and this is my pig."
One possible fix is to use an OrderedDict.
from collections import OrderedDict
def replace_all(text, dic):
for i, j in dic.items():
text = text.replace(i, j)
return text
od = OrderedDict([("cat", "dog"), ("dog", "pig")])
my_sentence = "This is my cat and this is my dog."
replace_all(my_sentence, od)
print(my_sentence)
Output:
"This is my pig and this is my pig."
Careful #2: Inefficient if your text string is too big or there are many pairs in the dictionary.
Why not one solution like this?
s = "The quick brown fox jumps over the lazy dog"
for r in (("brown", "red"), ("lazy", "quick")):
s = s.replace(*r)
#output will be: The quick red fox jumps over the quick dog
Here is a variant of the first solution using reduce, in case you like being functional. :)
repls = {'hello' : 'goodbye', 'world' : 'earth'}
s = 'hello, world'
reduce(lambda a, kv: a.replace(*kv), repls.iteritems(), s)
martineau's even better version:
repls = ('hello', 'goodbye'), ('world', 'earth')
s = 'hello, world'
reduce(lambda a, kv: a.replace(*kv), repls, s)
This is just a more concise recap of F.J and MiniQuark great answers and last but decisive improvement by bgusach. All you need to achieve multiple simultaneous string replacements is the following function:
def multiple_replace(string, rep_dict):
pattern = re.compile("|".join([re.escape(k) for k in sorted(rep_dict,key=len,reverse=True)]), flags=re.DOTALL)
return pattern.sub(lambda x: rep_dict[x.group(0)], string)
Usage:
>>>multiple_replace("Do you like cafe? No, I prefer tea.", {'cafe':'tea', 'tea':'cafe', 'like':'prefer'})
'Do you prefer tea? No, I prefer cafe.'
If you wish, you can make your own dedicated replacement functions starting from this simpler one.
Starting Python 3.8, and the introduction of assignment expressions (PEP 572) (:= operator), we can apply the replacements within a list comprehension:
# text = "The quick brown fox jumps over the lazy dog"
# replacements = [("brown", "red"), ("lazy", "quick")]
[text := text.replace(a, b) for a, b in replacements]
# text = 'The quick red fox jumps over the quick dog'
I built this upon F.J.s excellent answer:
import re
def multiple_replacer(*key_values):
replace_dict = dict(key_values)
replacement_function = lambda match: replace_dict[match.group(0)]
pattern = re.compile("|".join([re.escape(k) for k, v in key_values]), re.M)
return lambda string: pattern.sub(replacement_function, string)
def multiple_replace(string, *key_values):
return multiple_replacer(*key_values)(string)
One shot usage:
>>> replacements = (u"café", u"tea"), (u"tea", u"café"), (u"like", u"love")
>>> print multiple_replace(u"Do you like café? No, I prefer tea.", *replacements)
Do you love tea? No, I prefer café.
Note that since replacement is done in just one pass, "café" changes to "tea", but it does not change back to "café".
If you need to do the same replacement many times, you can create a replacement function easily:
>>> my_escaper = multiple_replacer(('"','\\"'), ('\t', '\\t'))
>>> many_many_strings = (u'This text will be escaped by "my_escaper"',
u'Does this work?\tYes it does',
u'And can we span\nmultiple lines?\t"Yes\twe\tcan!"')
>>> for line in many_many_strings:
... print my_escaper(line)
...
This text will be escaped by \"my_escaper\"
Does this work?\tYes it does
And can we span
multiple lines?\t\"Yes\twe\tcan!\"
Improvements:
turned code into a function
added multiline support
fixed a bug in escaping
easy to create a function for a specific multiple replacement
Enjoy! :-)
I would like to propose the usage of string templates. Just place the string to be replaced in a dictionary and all is set! Example from docs.python.org
>>> from string import Template
>>> s = Template('$who likes $what')
>>> s.substitute(who='tim', what='kung pao')
'tim likes kung pao'
>>> d = dict(who='tim')
>>> Template('Give $who $100').substitute(d)
Traceback (most recent call last):
[...]
ValueError: Invalid placeholder in string: line 1, col 10
>>> Template('$who likes $what').substitute(d)
Traceback (most recent call last):
[...]
KeyError: 'what'
>>> Template('$who likes $what').safe_substitute(d)
'tim likes $what'
In my case, I needed a simple replacing of unique keys with names, so I thought this up:
a = 'This is a test string.'
b = {'i': 'I', 's': 'S'}
for x,y in b.items():
a = a.replace(x, y)
>>> a
'ThIS IS a teSt StrIng.'
Here my $0.02. It is based on Andrew Clark's answer, just a little bit clearer, and it also covers the case when a string to replace is a substring of another string to replace (longer string wins)
def multireplace(string, replacements):
"""
Given a string and a replacement map, it returns the replaced string.
:param str string: string to execute replacements on
:param dict replacements: replacement dictionary {value to find: value to replace}
:rtype: str
"""
# Place longer ones first to keep shorter substrings from matching
# where the longer ones should take place
# For instance given the replacements {'ab': 'AB', 'abc': 'ABC'} against
# the string 'hey abc', it should produce 'hey ABC' and not 'hey ABc'
substrs = sorted(replacements, key=len, reverse=True)
# Create a big OR regex that matches any of the substrings to replace
regexp = re.compile('|'.join(map(re.escape, substrs)))
# For each match, look up the new string in the replacements
return regexp.sub(lambda match: replacements[match.group(0)], string)
It is in this this gist, feel free to modify it if you have any proposal.
I needed a solution where the strings to be replaced can be a regular expressions,
for example to help in normalizing a long text by replacing multiple whitespace characters with a single one. Building on a chain of answers from others, including MiniQuark and mmj, this is what I came up with:
def multiple_replace(string, reps, re_flags = 0):
""" Transforms string, replacing keys from re_str_dict with values.
reps: dictionary, or list of key-value pairs (to enforce ordering;
earlier items have higher priority).
Keys are used as regular expressions.
re_flags: interpretation of regular expressions, such as re.DOTALL
"""
if isinstance(reps, dict):
reps = reps.items()
pattern = re.compile("|".join("(?P<_%d>%s)" % (i, re_str[0])
for i, re_str in enumerate(reps)),
re_flags)
return pattern.sub(lambda x: reps[int(x.lastgroup[1:])][1], string)
It works for the examples given in other answers, for example:
>>> multiple_replace("(condition1) and --condition2--",
... {"condition1": "", "condition2": "text"})
'() and --text--'
>>> multiple_replace('hello, world', {'hello' : 'goodbye', 'world' : 'earth'})
'goodbye, earth'
>>> multiple_replace("Do you like cafe? No, I prefer tea.",
... {'cafe': 'tea', 'tea': 'cafe', 'like': 'prefer'})
'Do you prefer tea? No, I prefer cafe.'
The main thing for me is that you can use regular expressions as well, for example to replace whole words only, or to normalize white space:
>>> s = "I don't want to change this name:\n Philip II of Spain"
>>> re_str_dict = {r'\bI\b': 'You', r'[\n\t ]+': ' '}
>>> multiple_replace(s, re_str_dict)
"You don't want to change this name: Philip II of Spain"
If you want to use the dictionary keys as normal strings,
you can escape those before calling multiple_replace using e.g. this function:
def escape_keys(d):
""" transform dictionary d by applying re.escape to the keys """
return dict((re.escape(k), v) for k, v in d.items())
>>> multiple_replace(s, escape_keys(re_str_dict))
"I don't want to change this name:\n Philip II of Spain"
The following function can help in finding erroneous regular expressions among your dictionary keys (since the error message from multiple_replace isn't very telling):
def check_re_list(re_list):
""" Checks if each regular expression in list is well-formed. """
for i, e in enumerate(re_list):
try:
re.compile(e)
except (TypeError, re.error):
print("Invalid regular expression string "
"at position {}: '{}'".format(i, e))
>>> check_re_list(re_str_dict.keys())
Note that it does not chain the replacements, instead performs them simultaneously. This makes it more efficient without constraining what it can do. To mimic the effect of chaining, you may just need to add more string-replacement pairs and ensure the expected ordering of the pairs:
>>> multiple_replace("button", {"but": "mut", "mutton": "lamb"})
'mutton'
>>> multiple_replace("button", [("button", "lamb"),
... ("but", "mut"), ("mutton", "lamb")])
'lamb'
Note: Test your case, see comments.
Here's a sample which is more efficient on long strings with many small replacements.
source = "Here is foo, it does moo!"
replacements = {
'is': 'was', # replace 'is' with 'was'
'does': 'did',
'!': '?'
}
def replace(source, replacements):
finder = re.compile("|".join(re.escape(k) for k in replacements.keys())) # matches every string we want replaced
result = []
pos = 0
while True:
match = finder.search(source, pos)
if match:
# cut off the part up until match
result.append(source[pos : match.start()])
# cut off the matched part and replace it in place
result.append(replacements[source[match.start() : match.end()]])
pos = match.end()
else:
# the rest after the last match
result.append(source[pos:])
break
return "".join(result)
print replace(source, replacements)
The point is in avoiding many concatenations of long strings. We chop the source string to fragments, replacing some of the fragments as we form the list, and then join the whole thing back into a string.
I was doing a similar exercise in one of my school homework. This was my solution
dictionary = {1: ['hate', 'love'],
2: ['salad', 'burger'],
3: ['vegetables', 'pizza']}
def normalize(text):
for i in dictionary:
text = text.replace(dictionary[i][0], dictionary[i][1])
return text
See result yourself on test string
string_to_change = 'I hate salad and vegetables'
print(normalize(string_to_change))
You can use the pandas library and the replace function which supports both exact matches as well as regex replacements. For example:
df = pd.DataFrame({'text': ['Billy is going to visit Rome in November', 'I was born in 10/10/2010', 'I will be there at 20:00']})
to_replace=['Billy','Rome','January|February|March|April|May|June|July|August|September|October|November|December', '\d{2}:\d{2}', '\d{2}/\d{2}/\d{4}']
replace_with=['name','city','month','time', 'date']
print(df.text.replace(to_replace, replace_with, regex=True))
And the modified text is:
0 name is going to visit city in month
1 I was born in date
2 I will be there at time
You can find an example here. Notice that the replacements on the text are done with the order they appear in the lists
I was struggling with this problem as well. With many substitutions regular expressions struggle, and are about four times slower than looping string.replace (in my experiment conditions).
You should absolutely try using the Flashtext library (blog post here, Github here). In my case it was a bit over two orders of magnitude faster, from 1.8 s to 0.015 s (regular expressions took 7.7 s) for each document.
It is easy to find use examples in the links above, but this is a working example:
from flashtext import KeywordProcessor
self.processor = KeywordProcessor(case_sensitive=False)
for k, v in self.my_dict.items():
self.processor.add_keyword(k, v)
new_string = self.processor.replace_keywords(string)
Note that Flashtext makes substitutions in a single pass (to avoid a --> b and b --> c translating 'a' into 'c'). Flashtext also looks for whole words (so 'is' will not match 'this'). It works fine if your target is several words (replacing 'This is' by 'Hello').
I face similar problem today, where I had to do use .replace() method multiple times but it didn't feel good to me. So I did something like this:
REPLACEMENTS = {'<': '<', '>': '>', '&': '&'}
event_title = ''.join([REPLACEMENTS.get(c,c) for c in event['summary']])
I feel this question needs a single-line recursive lambda function answer for completeness, just because. So there:
>>> mrep = lambda s, d: s if not d else mrep(s.replace(*d.popitem()), d)
Usage:
>>> mrep('abcabc', {'a': '1', 'c': '2'})
'1b21b2'
Notes:
This consumes the input dictionary.
Python dicts preserve key order as of 3.6; corresponding caveats in other answers are not relevant anymore. For backward compatibility one could resort to a tuple-based version:
>>> mrep = lambda s, d: s if not d else mrep(s.replace(*d.pop()), d)
>>> mrep('abcabc', [('a', '1'), ('c', '2')])
Note: As with all recursive functions in python, too large recursion depth (i.e. too large replacement dictionaries) will result in an error. See e.g. here.
You should really not do it this way, but I just find it way too cool:
>>> replacements = {'cond1':'text1', 'cond2':'text2'}
>>> cmd = 'answer = s'
>>> for k,v in replacements.iteritems():
>>> cmd += ".replace(%s, %s)" %(k,v)
>>> exec(cmd)
Now, answer is the result of all the replacements in turn
again, this is very hacky and is not something that you should be using regularly. But it's just nice to know that you can do something like this if you ever need to.
For replace only one character, use the translate and str.maketrans is my favorite method.
tl;dr > result_string = your_string.translate(str.maketrans(dict_mapping))
demo
my_string = 'This is a test string.'
dict_mapping = {'i': 's', 's': 'S'}
result_good = my_string.translate(str.maketrans(dict_mapping))
result_bad = my_string
for x, y in dict_mapping.items():
result_bad = result_bad.replace(x, y)
print(result_good) # ThsS sS a teSt Strsng.
print(result_bad) # ThSS SS a teSt StrSng.
I don't know about speed but this is my workaday quick fix:
reduce(lambda a, b: a.replace(*b)
, [('o','W'), ('t','X')] #iterable of pairs: (oldval, newval)
, 'tomato' #The string from which to replace values
)
... but I like the #1 regex answer above. Note - if one new value is a substring of another one then the operation is not commutative.
Here is a version with support for basic regex replacement. The main restriction is that expressions must not contain subgroups, and there may be some edge cases:
Code based on #bgusach and others
import re
class StringReplacer:
def __init__(self, replacements, ignore_case=False):
patterns = sorted(replacements, key=len, reverse=True)
self.replacements = [replacements[k] for k in patterns]
re_mode = re.IGNORECASE if ignore_case else 0
self.pattern = re.compile('|'.join(("({})".format(p) for p in patterns)), re_mode)
def tr(matcher):
index = next((index for index,value in enumerate(matcher.groups()) if value), None)
return self.replacements[index]
self.tr = tr
def __call__(self, string):
return self.pattern.sub(self.tr, string)
Tests
table = {
"aaa" : "[This is three a]",
"b+" : "[This is one or more b]",
r"<\w+>" : "[This is a tag]"
}
replacer = StringReplacer(table, True)
sample1 = "whatever bb, aaa, <star> BBB <end>"
print(replacer(sample1))
# output:
# whatever [This is one or more b], [This is three a], [This is a tag] [This is one or more b] [This is a tag]
The trick is to identify the matched group by its position. It is not super efficient (O(n)), but it works.
index = next((index for index,value in enumerate(matcher.groups()) if value), None)
Replacement is done in one pass.
Starting from the precious answer of Andrew i developed a script that loads the dictionary from a file and elaborates all the files on the opened folder to do the replacements. The script loads the mappings from an external file in which you can set the separator. I'm a beginner but i found this script very useful when doing multiple substitutions in multiple files. It loaded a dictionary with more than 1000 entries in seconds. It is not elegant but it worked for me
import glob
import re
mapfile = input("Enter map file name with extension eg. codifica.txt: ")
sep = input("Enter map file column separator eg. |: ")
mask = input("Enter search mask with extension eg. 2010*txt for all files to be processed: ")
suff = input("Enter suffix with extension eg. _NEW.txt for newly generated files: ")
rep = {} # creation of empy dictionary
with open(mapfile) as temprep: # loading of definitions in the dictionary using input file, separator is prompted
for line in temprep:
(key, val) = line.strip('\n').split(sep)
rep[key] = val
for filename in glob.iglob(mask): # recursion on all the files with the mask prompted
with open (filename, "r") as textfile: # load each file in the variable text
text = textfile.read()
# start replacement
#rep = dict((re.escape(k), v) for k, v in rep.items()) commented to enable the use in the mapping of re reserved characters
pattern = re.compile("|".join(rep.keys()))
text = pattern.sub(lambda m: rep[m.group(0)], text)
#write of te output files with the prompted suffice
target = open(filename[:-4]+"_NEW.txt", "w")
target.write(text)
target.close()
this is my solution to the problem. I used it in a chatbot to replace the different words at once.
def mass_replace(text, dct):
new_string = ""
old_string = text
while len(old_string) > 0:
s = ""
sk = ""
for k in dct.keys():
if old_string.startswith(k):
s = dct[k]
sk = k
if s:
new_string+=s
old_string = old_string[len(sk):]
else:
new_string+=old_string[0]
old_string = old_string[1:]
return new_string
print mass_replace("The dog hunts the cat", {"dog":"cat", "cat":"dog"})
this will become The cat hunts the dog
Another example :
Input list
error_list = ['[br]', '[ex]', 'Something']
words = ['how', 'much[ex]', 'is[br]', 'the', 'fish[br]', 'noSomething', 'really']
The desired output would be
words = ['how', 'much', 'is', 'the', 'fish', 'no', 'really']
Code :
[n[0][0] if len(n[0]) else n[1] for n in [[[w.replace(e,"") for e in error_list if e in w],w] for w in words]]
My approach would be to first tokenize the string, then decide for each token whether to include it or not.
Potentially, might be more performant, if we can assume O(1) lookup for a hashmap/set:
remove_words = {"we", "this"}
target_sent = "we should modify this string"
target_sent_words = target_sent.split()
filtered_sent = " ".join(list(filter(lambda word: word not in remove_words, target_sent_words)))
filtered_sent is now 'should modify string'
Or just for a fast hack:
for line in to_read:
read_buffer = line
stripped_buffer1 = read_buffer.replace("term1", " ")
stripped_buffer2 = stripped_buffer1.replace("term2", " ")
write_to_file = to_write.write(stripped_buffer2)
Here is another way of doing it with a dictionary:
listA="The cat jumped over the house".split()
modify = {word:word for number,word in enumerate(listA)}
modify["cat"],modify["jumped"]="dog","walked"
print " ".join(modify[x] for x in listA)
sentence='its some sentence with a something text'
def replaceAll(f,Array1,Array2):
if len(Array1)==len(Array2):
for x in range(len(Array1)):
return f.replace(Array1[x],Array2[x])
newSentence=replaceAll(sentence,['a','sentence','something'],['another','sentence','something something'])
print(newSentence)
How do I count the number of occurrences of a character in a string?
e.g. 'a' appears in 'Mary had a little lamb' 4 times.
str.count(sub[, start[, end]])
Return the number of non-overlapping occurrences of substring sub in the range [start, end]. Optional arguments start and end are interpreted as in slice notation.
>>> sentence = 'Mary had a little lamb'
>>> sentence.count('a')
4
You can use .count() :
>>> 'Mary had a little lamb'.count('a')
4
To get the counts of all letters, use collections.Counter:
>>> from collections import Counter
>>> counter = Counter("Mary had a little lamb")
>>> counter['a']
4
Regular expressions maybe?
import re
my_string = "Mary had a little lamb"
len(re.findall("a", my_string))
Python-3.x:
"aabc".count("a")
str.count(sub[, start[, end]])
Return the number of non-overlapping occurrences of substring sub in the range [start, end]. Optional arguments start and end are interpreted as in slice notation.
myString.count('a');
more info here
str.count(a) is the best solution to count a single character in a string. But if you need to count more characters you would have to read the whole string as many times as characters you want to count.
A better approach for this job would be:
from collections import defaultdict
text = 'Mary had a little lamb'
chars = defaultdict(int)
for char in text:
chars[char] += 1
So you'll have a dict that returns the number of occurrences of every letter in the string and 0 if it isn't present.
>>>chars['a']
4
>>>chars['x']
0
For a case insensitive counter you could override the mutator and accessor methods by subclassing defaultdict (base class' ones are read-only):
class CICounter(defaultdict):
def __getitem__(self, k):
return super().__getitem__(k.lower())
def __setitem__(self, k, v):
super().__setitem__(k.lower(), v)
chars = CICounter(int)
for char in text:
chars[char] += 1
>>>chars['a']
4
>>>chars['M']
2
>>>chars['x']
0
This easy and straight forward function might help:
def check_freq(x):
freq = {}
for c in set(x):
freq[c] = x.count(c)
return freq
check_freq("abbabcbdbabdbdbabababcbcbab")
{'a': 7, 'b': 14, 'c': 3, 'd': 3}
If a comprehension is desired:
def check_freq(x):
return {c: x.count(c) for c in set(x)}
Regular expressions are very useful if you want case-insensitivity (and of course all the power of regex).
my_string = "Mary had a little lamb"
# simplest solution, using count, is case-sensitive
my_string.count("m") # yields 1
import re
# case-sensitive with regex
len(re.findall("m", my_string))
# three ways to get case insensitivity - all yield 2
len(re.findall("(?i)m", my_string))
len(re.findall("m|M", my_string))
len(re.findall(re.compile("m",re.IGNORECASE), my_string))
Be aware that the regex version takes on the order of ten times as long to run, which will likely be an issue only if my_string is tremendously long, or the code is inside a deep loop.
I don't know about 'simplest' but simple comprehension could do:
>>> my_string = "Mary had a little lamb"
>>> sum(char == 'a' for char in my_string)
4
Taking advantage of built-in sum, generator comprehension and fact that bool is subclass of integer: how may times character is equal to 'a'.
a = 'have a nice day'
symbol = 'abcdefghijklmnopqrstuvwxyz'
for key in symbol:
print(key, a.count(key))
An alternative way to get all the character counts without using Counter(), count and regex
counts_dict = {}
for c in list(sentence):
if c not in counts_dict:
counts_dict[c] = 0
counts_dict[c] += 1
for key, value in counts_dict.items():
print(key, value)
I am a fan of the pandas library, in particular the value_counts() method. You could use it to count the occurrence of each character in your string:
>>> import pandas as pd
>>> phrase = "I love the pandas library and its `value_counts()` method"
>>> pd.Series(list(phrase)).value_counts()
8
a 5
e 4
t 4
o 3
n 3
s 3
d 3
l 3
u 2
i 2
r 2
v 2
` 2
h 2
p 1
b 1
I 1
m 1
( 1
y 1
_ 1
) 1
c 1
dtype: int64
count is definitely the most concise and efficient way of counting the occurrence of a character in a string but I tried to come up with a solution using lambda, something like this :
sentence = 'Mary had a little lamb'
sum(map(lambda x : 1 if 'a' in x else 0, sentence))
This will result in :
4
Also, there is one more advantage to this is if the sentence is a list of sub-strings containing same characters as above, then also this gives the correct result because of the use of in. Have a look :
sentence = ['M', 'ar', 'y', 'had', 'a', 'little', 'l', 'am', 'b']
sum(map(lambda x : 1 if 'a' in x else 0, sentence))
This also results in :
4
But Of-course this will work only when checking occurrence of single character such as 'a' in this particular case.
a = "I walked today,"
c=['d','e','f']
count=0
for i in a:
if str(i) in c:
count+=1
print(count)
I know the ask is to count a particular letter. I am writing here generic code without using any method.
sentence1 =" Mary had a little lamb"
count = {}
for i in sentence1:
if i in count:
count[i.lower()] = count[i.lower()] + 1
else:
count[i.lower()] = 1
print(count)
output
{' ': 5, 'm': 2, 'a': 4, 'r': 1, 'y': 1, 'h': 1, 'd': 1, 'l': 3, 'i': 1, 't': 2, 'e': 1, 'b': 1}
Now if you want any particular letter frequency, you can print like below.
print(count['m'])
2
the easiest way is to code in one line:
'Mary had a little lamb'.count("a")
but if you want can use this too:
sentence ='Mary had a little lamb'
count=0;
for letter in sentence :
if letter=="a":
count+=1
print (count)
To find the occurrence of characters in a sentence you may use the below code
Firstly, I have taken out the unique characters from the sentence and then I counted the occurrence of each character in the sentence these includes the occurrence of blank space too.
ab = set("Mary had a little lamb")
test_str = "Mary had a little lamb"
for i in ab:
counter = test_str.count(i)
if i == ' ':
i = 'Space'
print(counter, i)
Output of the above code is below.
1 : r ,
1 : h ,
1 : e ,
1 : M ,
4 : a ,
1 : b ,
1 : d ,
2 : t ,
3 : l ,
1 : i ,
4 : Space ,
1 : y ,
1 : m ,
"Without using count to find you want character in string" method.
import re
def count(s, ch):
pass
def main():
s = raw_input ("Enter strings what you like, for example, 'welcome': ")
ch = raw_input ("Enter you want count characters, but best result to find one character: " )
print ( len (re.findall ( ch, s ) ) )
main()
Python 3
Ther are two ways to achieve this:
1) With built-in function count()
sentence = 'Mary had a little lamb'
print(sentence.count('a'))`
2) Without using a function
sentence = 'Mary had a little lamb'
count = 0
for i in sentence:
if i == "a":
count = count + 1
print(count)
Use count:
sentence = 'A man walked up to a door'
print(sentence.count('a'))
# 4
Taking up a comment of this user:
import numpy as np
sample = 'samplestring'
np.unique(list(sample), return_counts=True)
Out:
(array(['a', 'e', 'g', 'i', 'l', 'm', 'n', 'p', 'r', 's', 't'], dtype='<U1'),
array([1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1]))
Check 's'. You can filter this tuple of two arrays as follows:
a[1][a[0]=='s']
Side-note: It works like Counter() of the collections package, just in numpy, which you often import anyway. You could as well count the unique words in a list of words instead.
This is an extension of the accepted answer, should you look for the count of all the characters in the text.
# Objective: we will only count for non-empty characters
text = "count a character occurrence"
unique_letters = set(text)
result = dict((x, text.count(x)) for x in unique_letters if x.strip())
print(result)
# {'a': 3, 'c': 6, 'e': 3, 'u': 2, 'n': 2, 't': 2, 'r': 3, 'h': 1, 'o': 2}
No more than this IMHO - you can add the upper or lower methods
def count_letter_in_str(string,letter):
return string.count(letter)
You can use loop and dictionary.
def count_letter(text):
result = {}
for letter in text:
if letter not in result:
result[letter] = 0
result[letter] += 1
return result
spam = 'have a nice day'
var = 'd'
def count(spam, var):
found = 0
for key in spam:
if key == var:
found += 1
return found
count(spam, var)
print 'count %s is: %s ' %(var, count(spam, var))
Given a vocabulary ["NY", "LA", "GA"],
how can one encode it in such a way that it becomes:
"NY" = 100
"LA" = 010
"GA" = 001
So if I do a lookup on "NY GA", I get 101
you can use numpy.in1d:
>>> xs = np.array(["NY", "LA", "GA"])
>>> ''.join('1' if f else '0' for f in np.in1d(xs, 'NY GA'.split(' ')))
'101'
or:
>>> ''.join(np.where(np.in1d(xs, 'NY GA'.split(' ')), '1', '0'))
'101'
vocab = ["NY", "LA", "GA"]
categorystring = '0'*len(vocab)
selectedVocabs = 'NY GA'
for sel in selectedVocabs.split():
categorystring = list(categorystring)
categorystring[vocab.index(sel)] = '1'
categorystring = ''.join(categorystring)
This is the end result of my won testing, turns out Python doesn't support string item assignment, somehow i thought it did.
Personally i think behzad's solution is better, numpy does a better job and is faster.
Or you can
vocabulary = ["NY","LA","GA"]
i=pow(10,len(vocabulary)-1)
dictVocab = dict()
for word in vocabulary:
dictVocab[word] = i
i /= 10
yourStr = "NY LA"
result = 0
for word in yourStr.split():
result += dictVocab[word]
Another solution using numpy. It looks like you're tyring to binary encode a dictionary, so the code below feels natural to me.
import numpy as np
def to_binary_representation(your_str="NY LA"):
xs = np.array(["NY", "LA", "GA"])
ys = 2**np.arange(3)[::-1]
lookup_table = dict(zip(xs,ys))
return bin(np.sum([lookup_table[k] for k in your_str.split()]))
It's also not needed to do it in numpy, but it is probably faster in case you have large arrays to work on. np.sum can be replaced by the builtin sum then and the xs and ys can be transformed to non-numpy equivalents.
To create a lookup dictionary, reverse the vocabulary, enumerate it, and take the power of 2:
>>> vocabulary = ["NY", "LA", "GA"]
d = dict((word, 2 ** i) for i, word in enumerate(reversed(vocabulary)))
>>> d
{'NY': 4, 'GA': 1, 'LA': 2}
To query the dictionary:
>>> query = "NY GA"
>>> sum(code for word, code in d.iteritems() if word in query.split())
5
If you want it formatted to binary:
>>> '{0:b}'.format(5)
'101'
edit: if you want a 'one liner':
>>> '{0:b}'.format(
sum(2 ** i
for i, word in enumerate(reversed(vocabulary))
if word in query.split()))
'101'
edit2: if you want padding, for example with six 'bits':
>>> '{0:06b}'.format(5)
'000101'