Mixing
Split string from a preset list of strings from pandas df column
3
I have a pandas dataframe that looks like below. It has about a million rows.
name = ['Jake','Matt', 'Henry']
0 A
1 Jake Hill
2 Matt Dawn
3 Matt King
4 White Henry
5 Hyde Jake
I want to iterate over the list and the df['A'] column and return only the first names. For example, the final dataframe should look like this.
0 A
1 Jake
2 Matt
3 Matt
4 Henry
5 Jake
Thanks in advance. I am new to python so still figuring out the easiest way to do this.
python python-3.x pandas python-2.7
asked Nov 20 '18 at 5:29
MattMatt
546
add a comment |
3
I have a pandas dataframe that looks like below. It has about a million rows.
name = ['Jake','Matt', 'Henry']
0 A
1 Jake Hill
2 Matt Dawn
3 Matt King
4 White Henry
5 Hyde Jake
I want to iterate over the list and the df['A'] column and return only the first names. For example, the final dataframe should look like this.
0 A
1 Jake
2 Matt
3 Matt
4 Henry
5 Jake
Thanks in advance. I am new to python so still figuring out the easiest way to do this.
python python-3.x pandas python-2.7
asked Nov 20 '18 at 5:29
MattMatt
546
2
what if value of column A doesn't exist in list?
– AkshayNevrekar
Nov 20 '18 at 5:31
1
What about first names that aren't Jake,Matt,Henry ? Do you want to filter them out?
– CIsForCookies
Nov 20 '18 at 5:31
Then the original name should be retained. For example if the name is Dave Atkins then it should retain the name Dave Atkins but I have made sure that I have all the names. So that should not be a problem.
– Matt
Nov 20 '18 at 5:33
add a comment |
3
3
3
I have a pandas dataframe that looks like below. It has about a million rows.
name = ['Jake','Matt', 'Henry']
0 A
1 Jake Hill
2 Matt Dawn
3 Matt King
4 White Henry
5 Hyde Jake
I want to iterate over the list and the df['A'] column and return only the first names. For example, the final dataframe should look like this.
0 A
1 Jake
2 Matt
3 Matt
4 Henry
5 Jake
Thanks in advance. I am new to python so still figuring out the easiest way to do this.
python python-3.x pandas python-2.7
asked Nov 20 '18 at 5:29
MattMatt
546
I have a pandas dataframe that looks like below. It has about a million rows.
name = ['Jake','Matt', 'Henry']
0 A
1 Jake Hill
2 Matt Dawn
3 Matt King
4 White Henry
5 Hyde Jake
I want to iterate over the list and the df['A'] column and return only the first names. For example, the final dataframe should look like this.
0 A
1 Jake
2 Matt
3 Matt
4 Henry
5 Jake
Thanks in advance. I am new to python so still figuring out the easiest way to do this.
python python-3.x pandas python-2.7
python python-3.x pandas python-2.7
asked Nov 20 '18 at 5:29
MattMatt
546
asked Nov 20 '18 at 5:29
MattMatt
546
edited Nov 20 '18 at 5:45
Matt
asked Nov 20 '18 at 5:29
MattMatt
546
asked Nov 20 '18 at 5:29
MattMatt
546
asked Nov 20 '18 at 5:29
MattMatt
546
546
2
what if value of column A doesn't exist in list?
– AkshayNevrekar
Nov 20 '18 at 5:31
1
What about first names that aren't Jake,Matt,Henry ? Do you want to filter them out?
– CIsForCookies
Nov 20 '18 at 5:31
Then the original name should be retained. For example if the name is Dave Atkins then it should retain the name Dave Atkins but I have made sure that I have all the names. So that should not be a problem.
– Matt
Nov 20 '18 at 5:33
add a comment |
2
what if value of column A doesn't exist in list?
– AkshayNevrekar
Nov 20 '18 at 5:31
1
What about first names that aren't Jake,Matt,Henry ? Do you want to filter them out?
– CIsForCookies
Nov 20 '18 at 5:31
Then the original name should be retained. For example if the name is Dave Atkins then it should retain the name Dave Atkins but I have made sure that I have all the names. So that should not be a problem.
– Matt
Nov 20 '18 at 5:33
2
2
what if value of column A doesn't exist in list?
– AkshayNevrekar
Nov 20 '18 at 5:31
what if value of column A doesn't exist in list?
– AkshayNevrekar
Nov 20 '18 at 5:31
1
1
What about first names that aren't Jake,Matt,Henry ? Do you want to filter them out?
– CIsForCookies
Nov 20 '18 at 5:31
What about first names that aren't Jake,Matt,Henry ? Do you want to filter them out?
– CIsForCookies
Nov 20 '18 at 5:31
Then the original name should be retained. For example if the name is Dave Atkins then it should retain the name Dave Atkins but I have made sure that I have all the names. So that should not be a problem.
– Matt
Nov 20 '18 at 5:33
Then the original name should be retained. For example if the name is Dave Atkins then it should retain the name Dave Atkins but I have made sure that I have all the names. So that should not be a problem.
– Matt
Nov 20 '18 at 5:33
add a comment |
7 Answers
7
active
oldest
votes
2
You need:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White','Jake Hyde','Dwayne John']})
def func(x):
for k in first_name:
if k in x:
return k
return x
df['A'] = df['A'].apply(lambda x: func(x))
Output:
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
5 Dwayne John
answered Nov 20 '18 at 5:37
AkshayNevrekarAkshayNevrekar
4,14491735
Hey. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:48
add a comment |
3
You have a list of names to match, and a Series of names to check against. Use a regular expression with str.extract here.
df.A.str.extract(r'({})'.format('|'.join(name)))
0
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
answered Nov 20 '18 at 5:59
user3483203user3483203
30.8k82454
add a comment |
2
Here is one method to achieve this:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White', 'Jake Hyde']})
df['B'] = df['A'].str.split().apply(lambda x: x[0] if x[0] in first_name else ' '.join(x))
and you get:
A B
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Jake Hyde Jake
answered Nov 20 '18 at 5:37
Gerges DibGerges Dib
3,0181820
Hey Gerges. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:46
add a comment |
0
name = ['Jake','Matt', 'Henry']
df = pd.read_csv("file.csv")
#filling nan values in-case if it is there
df.fillna(0, inplace = True)
df["First Name"] = df.A.apply(lambda x: list(set(x.split(" ")) & set(name))[0] if x != 0 else "Not Found")
Output:
A First Name
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Hyde Jake Jake
answered Nov 20 '18 at 5:40
Srce CdeSrce Cde
1,164511
Hey Chirag. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:47
add a comment |
0
Try using:
A_final=A[0].str.split(' ',expand=True, n=1).str.get(0)
A_final[0]
, your problem is resolved.
answered Nov 20 '18 at 6:01
Jeet BhattachariyaJeet Bhattachariya
11
What is this doing?
– pygo
Nov 20 '18 at 6:03
add a comment |
0
In addition to earlier edit, Which i understood now you want to inplace replacement, Which can be done with list comprehension as follows with splitting the column A Fist and choose the First Index of of it and passing to lambda using apply method.
DataFrame Structure:
df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
Your name Var..
$ name
['Jake', 'Matt', 'Henry']
Your Final desired Dataset:
Parameter n can be used to limit the number of splits in the output.
df['A'] = df['A'].str.split(n=1, expand=True)[0].apply(lambda x: x if x in name else ' '.join(x))
print(df)
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
It should be simple if you not pressed to take names from a Var and end goal is to get the First name from the dataframe :
>>> df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
>>> df['A'].str.split(n=1, expand=True)[0]
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
Name: 0, dtype: object
OR In case you want inplace replacement for column A ..
df['A'] = df['A'].str.split(n=1, expand=True)[0]
answered Nov 20 '18 at 5:44
pygopygo
3,0551619
your input df is different from the user input. In this problem first name is customised.
– Mohamed Thasin ah
Nov 20 '18 at 5:59
@MohamedThasinah, thnx for the feedback but did not get you, but intent is same.
– pygo
Nov 20 '18 at 6:00
In your input df at 3 rd index, user provides asWhite Henrybut you took it asHenry White.
– Mohamed Thasin ah
Nov 20 '18 at 6:02
add a comment |
0
This method won't be fooled by a last name containing one of the first name strings, such as "Matten" or "Jakes", and will combine a first and last name if they are both found in the first names list, such as "Matt Henry" (shows "MattHenry" in the output dataframe).
# split the name strings into columns as new dataframe
df1 = df.A.str.split(' ', expand=True)
# Keep the first names in the new dataframe and fill the rest with
# empty strings, then sum the df1 column string values to make a new array
names_result = np.where(df1.isin(name), df1, '').sum(axis=1)
# find the array indexes where no first names were found
no_match_idx = np.where(names_result == '')[0]
# fill the no first name index locations with original dataframe values
names_result[no_match_idx] = df.A.values[no_match_idx]
# make a dataframe using the results
df_out = pd.DataFrame(names_result, columns=['A'])
# to find names with a first and last name that are both found in the
# first names list:
# df_out['dups'] = df1.isin(name).sum(axis=1) > 1
answered Nov 21 '18 at 2:00
b2002b2002
546148
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
draft saved
draft discarded
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53386763%2fsplit-string-from-a-preset-list-of-strings-from-pandas-df-column%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
7 Answers
7
active
oldest
votes
7 Answers
7
active
oldest
votes
active
oldest
votes
active
oldest
votes
2
You need:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White','Jake Hyde','Dwayne John']})
def func(x):
for k in first_name:
if k in x:
return k
return x
df['A'] = df['A'].apply(lambda x: func(x))
Output:
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
5 Dwayne John
answered Nov 20 '18 at 5:37
AkshayNevrekarAkshayNevrekar
4,14491735
Hey. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:48
add a comment |
2
You need:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White','Jake Hyde','Dwayne John']})
def func(x):
for k in first_name:
if k in x:
return k
return x
df['A'] = df['A'].apply(lambda x: func(x))
Output:
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
5 Dwayne John
answered Nov 20 '18 at 5:37
AkshayNevrekarAkshayNevrekar
4,14491735
Hey. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:48
add a comment |
2
2
2
You need:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White','Jake Hyde','Dwayne John']})
def func(x):
for k in first_name:
if k in x:
return k
return x
df['A'] = df['A'].apply(lambda x: func(x))
Output:
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
5 Dwayne John
answered Nov 20 '18 at 5:37
AkshayNevrekarAkshayNevrekar
4,14491735
You need:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White','Jake Hyde','Dwayne John']})
def func(x):
for k in first_name:
if k in x:
return k
return x
df['A'] = df['A'].apply(lambda x: func(x))
Output:
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
5 Dwayne John
answered Nov 20 '18 at 5:37
AkshayNevrekarAkshayNevrekar
4,14491735
edited Nov 20 '18 at 5:53
answered Nov 20 '18 at 5:37
AkshayNevrekarAkshayNevrekar
4,14491735
answered Nov 20 '18 at 5:37
AkshayNevrekarAkshayNevrekar
4,14491735
answered Nov 20 '18 at 5:37
AkshayNevrekarAkshayNevrekar
4,14491735
4,14491735
Hey. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:48
add a comment |
Hey. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:48
Hey. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:48
Hey. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:48
add a comment |
3
You have a list of names to match, and a Series of names to check against. Use a regular expression with str.extract here.
df.A.str.extract(r'({})'.format('|'.join(name)))
0
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
answered Nov 20 '18 at 5:59
user3483203user3483203
30.8k82454
add a comment |
3
You have a list of names to match, and a Series of names to check against. Use a regular expression with str.extract here.
df.A.str.extract(r'({})'.format('|'.join(name)))
0
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
answered Nov 20 '18 at 5:59
user3483203user3483203
30.8k82454
add a comment |
3
3
3
You have a list of names to match, and a Series of names to check against. Use a regular expression with str.extract here.
df.A.str.extract(r'({})'.format('|'.join(name)))
0
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
answered Nov 20 '18 at 5:59
user3483203user3483203
30.8k82454
You have a list of names to match, and a Series of names to check against. Use a regular expression with str.extract here.
df.A.str.extract(r'({})'.format('|'.join(name)))
0
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
answered Nov 20 '18 at 5:59
user3483203user3483203
30.8k82454
answered Nov 20 '18 at 5:59
user3483203user3483203
30.8k82454
answered Nov 20 '18 at 5:59
user3483203user3483203
30.8k82454
answered Nov 20 '18 at 5:59
user3483203user3483203
30.8k82454
30.8k82454
add a comment |
add a comment |
2
Here is one method to achieve this:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White', 'Jake Hyde']})
df['B'] = df['A'].str.split().apply(lambda x: x[0] if x[0] in first_name else ' '.join(x))
and you get:
A B
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Jake Hyde Jake
answered Nov 20 '18 at 5:37
Gerges DibGerges Dib
3,0181820
Hey Gerges. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:46
add a comment |
2
Here is one method to achieve this:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White', 'Jake Hyde']})
df['B'] = df['A'].str.split().apply(lambda x: x[0] if x[0] in first_name else ' '.join(x))
and you get:
A B
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Jake Hyde Jake
answered Nov 20 '18 at 5:37
Gerges DibGerges Dib
3,0181820
Hey Gerges. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:46
add a comment |
2
2
2
Here is one method to achieve this:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White', 'Jake Hyde']})
df['B'] = df['A'].str.split().apply(lambda x: x[0] if x[0] in first_name else ' '.join(x))
and you get:
A B
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Jake Hyde Jake
answered Nov 20 '18 at 5:37
Gerges DibGerges Dib
3,0181820
Here is one method to achieve this:
first_name = ['Jake','Matt', 'Henry']
df = pd.DataFrame({'A': ['Jake Hill', 'Matt Dawn', 'Matt King', 'Henry White', 'Jake Hyde']})
df['B'] = df['A'].str.split().apply(lambda x: x[0] if x[0] in first_name else ' '.join(x))
and you get:
A B
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Jake Hyde Jake
answered Nov 20 '18 at 5:37
Gerges DibGerges Dib
3,0181820
answered Nov 20 '18 at 5:37
Gerges DibGerges Dib
3,0181820
answered Nov 20 '18 at 5:37
Gerges DibGerges Dib
3,0181820
answered Nov 20 '18 at 5:37
Gerges DibGerges Dib
3,0181820
3,0181820
Hey Gerges. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:46
add a comment |
Hey Gerges. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:46
Hey Gerges. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:46
Hey Gerges. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:46
add a comment |
0
name = ['Jake','Matt', 'Henry']
df = pd.read_csv("file.csv")
#filling nan values in-case if it is there
df.fillna(0, inplace = True)
df["First Name"] = df.A.apply(lambda x: list(set(x.split(" ")) & set(name))[0] if x != 0 else "Not Found")
Output:
A First Name
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Hyde Jake Jake
answered Nov 20 '18 at 5:40
Srce CdeSrce Cde
1,164511
Hey Chirag. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:47
add a comment |
0
name = ['Jake','Matt', 'Henry']
df = pd.read_csv("file.csv")
#filling nan values in-case if it is there
df.fillna(0, inplace = True)
df["First Name"] = df.A.apply(lambda x: list(set(x.split(" ")) & set(name))[0] if x != 0 else "Not Found")
Output:
A First Name
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Hyde Jake Jake
answered Nov 20 '18 at 5:40
Srce CdeSrce Cde
1,164511
Hey Chirag. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:47
add a comment |
0
0
0
name = ['Jake','Matt', 'Henry']
df = pd.read_csv("file.csv")
#filling nan values in-case if it is there
df.fillna(0, inplace = True)
df["First Name"] = df.A.apply(lambda x: list(set(x.split(" ")) & set(name))[0] if x != 0 else "Not Found")
Output:
A First Name
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Hyde Jake Jake
answered Nov 20 '18 at 5:40
Srce CdeSrce Cde
1,164511
name = ['Jake','Matt', 'Henry']
df = pd.read_csv("file.csv")
#filling nan values in-case if it is there
df.fillna(0, inplace = True)
df["First Name"] = df.A.apply(lambda x: list(set(x.split(" ")) & set(name))[0] if x != 0 else "Not Found")
Output:
A First Name
0 Jake Hill Jake
1 Matt Dawn Matt
2 Matt King Matt
3 Henry White Henry
4 Hyde Jake Jake
answered Nov 20 '18 at 5:40
Srce CdeSrce Cde
1,164511
edited Nov 20 '18 at 5:51
answered Nov 20 '18 at 5:40
Srce CdeSrce Cde
1,164511
answered Nov 20 '18 at 5:40
Srce CdeSrce Cde
1,164511
answered Nov 20 '18 at 5:40
Srce CdeSrce Cde
1,164511
1,164511
Hey Chirag. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:47
add a comment |
Hey Chirag. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:47
Hey Chirag. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:47
Hey Chirag. This specifically takes the first string after the split but it does not work if you have to extract a specific string from the column rows. I edited the question a little bit. Please have a look.
– Matt
Nov 20 '18 at 5:47
add a comment |
0
Try using:
A_final=A[0].str.split(' ',expand=True, n=1).str.get(0)
A_final[0]
, your problem is resolved.
answered Nov 20 '18 at 6:01
Jeet BhattachariyaJeet Bhattachariya
11
What is this doing?
– pygo
Nov 20 '18 at 6:03
add a comment |
0
Try using:
A_final=A[0].str.split(' ',expand=True, n=1).str.get(0)
A_final[0]
, your problem is resolved.
answered Nov 20 '18 at 6:01
Jeet BhattachariyaJeet Bhattachariya
11
What is this doing?
– pygo
Nov 20 '18 at 6:03
add a comment |
0
0
0
Try using:
A_final=A[0].str.split(' ',expand=True, n=1).str.get(0)
A_final[0]
, your problem is resolved.
answered Nov 20 '18 at 6:01
Jeet BhattachariyaJeet Bhattachariya
11
Try using:
A_final=A[0].str.split(' ',expand=True, n=1).str.get(0)
A_final[0]
, your problem is resolved.
answered Nov 20 '18 at 6:01
Jeet BhattachariyaJeet Bhattachariya
11
edited Nov 20 '18 at 6:05
answered Nov 20 '18 at 6:01
Jeet BhattachariyaJeet Bhattachariya
11
answered Nov 20 '18 at 6:01
Jeet BhattachariyaJeet Bhattachariya
11
answered Nov 20 '18 at 6:01
Jeet BhattachariyaJeet Bhattachariya
11
11
What is this doing?
– pygo
Nov 20 '18 at 6:03
add a comment |
What is this doing?
– pygo
Nov 20 '18 at 6:03
What is this doing?
– pygo
Nov 20 '18 at 6:03
What is this doing?
– pygo
Nov 20 '18 at 6:03
add a comment |
0
In addition to earlier edit, Which i understood now you want to inplace replacement, Which can be done with list comprehension as follows with splitting the column A Fist and choose the First Index of of it and passing to lambda using apply method.
DataFrame Structure:
df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
Your name Var..
$ name
['Jake', 'Matt', 'Henry']
Your Final desired Dataset:
Parameter n can be used to limit the number of splits in the output.
df['A'] = df['A'].str.split(n=1, expand=True)[0].apply(lambda x: x if x in name else ' '.join(x))
print(df)
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
It should be simple if you not pressed to take names from a Var and end goal is to get the First name from the dataframe :
>>> df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
>>> df['A'].str.split(n=1, expand=True)[0]
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
Name: 0, dtype: object
OR In case you want inplace replacement for column A ..
df['A'] = df['A'].str.split(n=1, expand=True)[0]
answered Nov 20 '18 at 5:44
pygopygo
3,0551619
your input df is different from the user input. In this problem first name is customised.
– Mohamed Thasin ah
Nov 20 '18 at 5:59
@MohamedThasinah, thnx for the feedback but did not get you, but intent is same.
– pygo
Nov 20 '18 at 6:00
In your input df at 3 rd index, user provides asWhite Henrybut you took it asHenry White.
– Mohamed Thasin ah
Nov 20 '18 at 6:02
add a comment |
0
In addition to earlier edit, Which i understood now you want to inplace replacement, Which can be done with list comprehension as follows with splitting the column A Fist and choose the First Index of of it and passing to lambda using apply method.
DataFrame Structure:
df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
Your name Var..
$ name
['Jake', 'Matt', 'Henry']
Your Final desired Dataset:
Parameter n can be used to limit the number of splits in the output.
df['A'] = df['A'].str.split(n=1, expand=True)[0].apply(lambda x: x if x in name else ' '.join(x))
print(df)
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
It should be simple if you not pressed to take names from a Var and end goal is to get the First name from the dataframe :
>>> df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
>>> df['A'].str.split(n=1, expand=True)[0]
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
Name: 0, dtype: object
OR In case you want inplace replacement for column A ..
df['A'] = df['A'].str.split(n=1, expand=True)[0]
answered Nov 20 '18 at 5:44
pygopygo
3,0551619
your input df is different from the user input. In this problem first name is customised.
– Mohamed Thasin ah
Nov 20 '18 at 5:59
@MohamedThasinah, thnx for the feedback but did not get you, but intent is same.
– pygo
Nov 20 '18 at 6:00
In your input df at 3 rd index, user provides asWhite Henrybut you took it asHenry White.
– Mohamed Thasin ah
Nov 20 '18 at 6:02
add a comment |
0
0
0
In addition to earlier edit, Which i understood now you want to inplace replacement, Which can be done with list comprehension as follows with splitting the column A Fist and choose the First Index of of it and passing to lambda using apply method.
DataFrame Structure:
df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
Your name Var..
$ name
['Jake', 'Matt', 'Henry']
Your Final desired Dataset:
Parameter n can be used to limit the number of splits in the output.
df['A'] = df['A'].str.split(n=1, expand=True)[0].apply(lambda x: x if x in name else ' '.join(x))
print(df)
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
It should be simple if you not pressed to take names from a Var and end goal is to get the First name from the dataframe :
>>> df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
>>> df['A'].str.split(n=1, expand=True)[0]
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
Name: 0, dtype: object
OR In case you want inplace replacement for column A ..
df['A'] = df['A'].str.split(n=1, expand=True)[0]
answered Nov 20 '18 at 5:44
pygopygo
3,0551619
In addition to earlier edit, Which i understood now you want to inplace replacement, Which can be done with list comprehension as follows with splitting the column A Fist and choose the First Index of of it and passing to lambda using apply method.
DataFrame Structure:
df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
Your name Var..
$ name
['Jake', 'Matt', 'Henry']
Your Final desired Dataset:
Parameter n can be used to limit the number of splits in the output.
df['A'] = df['A'].str.split(n=1, expand=True)[0].apply(lambda x: x if x in name else ' '.join(x))
print(df)
A
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
It should be simple if you not pressed to take names from a Var and end goal is to get the First name from the dataframe :
>>> df
A
0 Jake Hill
1 Matt Dawn
2 Matt King
3 Henry White
4 Jake Hyde
>>> df['A'].str.split(n=1, expand=True)[0]
0 Jake
1 Matt
2 Matt
3 Henry
4 Jake
Name: 0, dtype: object
OR In case you want inplace replacement for column A ..
df['A'] = df['A'].str.split(n=1, expand=True)[0]
answered Nov 20 '18 at 5:44
pygopygo
3,0551619
edited Nov 20 '18 at 6:55
answered Nov 20 '18 at 5:44
pygopygo
3,0551619
answered Nov 20 '18 at 5:44
pygopygo
3,0551619
answered Nov 20 '18 at 5:44
pygopygo
3,0551619
3,0551619
your input df is different from the user input. In this problem first name is customised.
– Mohamed Thasin ah
Nov 20 '18 at 5:59
@MohamedThasinah, thnx for the feedback but did not get you, but intent is same.
– pygo
Nov 20 '18 at 6:00
In your input df at 3 rd index, user provides asWhite Henrybut you took it asHenry White.
– Mohamed Thasin ah
Nov 20 '18 at 6:02
add a comment |
your input df is different from the user input. In this problem first name is customised.
– Mohamed Thasin ah
Nov 20 '18 at 5:59
@MohamedThasinah, thnx for the feedback but did not get you, but intent is same.
– pygo
Nov 20 '18 at 6:00
In your input df at 3 rd index, user provides asWhite Henrybut you took it asHenry White.
– Mohamed Thasin ah
Nov 20 '18 at 6:02
your input df is different from the user input. In this problem first name is customised.
– Mohamed Thasin ah
Nov 20 '18 at 5:59
your input df is different from the user input. In this problem first name is customised.
– Mohamed Thasin ah
Nov 20 '18 at 5:59
@MohamedThasinah, thnx for the feedback but did not get you, but intent is same.
– pygo
Nov 20 '18 at 6:00
@MohamedThasinah, thnx for the feedback but did not get you, but intent is same.
– pygo
Nov 20 '18 at 6:00
In your input df at 3 rd index, user provides as
White Henry but you took it as Henry White.– Mohamed Thasin ah
Nov 20 '18 at 6:02
In your input df at 3 rd index, user provides as
White Henry but you took it as Henry White.– Mohamed Thasin ah
Nov 20 '18 at 6:02
add a comment |
0
This method won't be fooled by a last name containing one of the first name strings, such as "Matten" or "Jakes", and will combine a first and last name if they are both found in the first names list, such as "Matt Henry" (shows "MattHenry" in the output dataframe).
# split the name strings into columns as new dataframe
df1 = df.A.str.split(' ', expand=True)
# Keep the first names in the new dataframe and fill the rest with
# empty strings, then sum the df1 column string values to make a new array
names_result = np.where(df1.isin(name), df1, '').sum(axis=1)
# find the array indexes where no first names were found
no_match_idx = np.where(names_result == '')[0]
# fill the no first name index locations with original dataframe values
names_result[no_match_idx] = df.A.values[no_match_idx]
# make a dataframe using the results
df_out = pd.DataFrame(names_result, columns=['A'])
# to find names with a first and last name that are both found in the
# first names list:
# df_out['dups'] = df1.isin(name).sum(axis=1) > 1
answered Nov 21 '18 at 2:00
b2002b2002
546148
add a comment |
0
This method won't be fooled by a last name containing one of the first name strings, such as "Matten" or "Jakes", and will combine a first and last name if they are both found in the first names list, such as "Matt Henry" (shows "MattHenry" in the output dataframe).
# split the name strings into columns as new dataframe
df1 = df.A.str.split(' ', expand=True)
# Keep the first names in the new dataframe and fill the rest with
# empty strings, then sum the df1 column string values to make a new array
names_result = np.where(df1.isin(name), df1, '').sum(axis=1)
# find the array indexes where no first names were found
no_match_idx = np.where(names_result == '')[0]
# fill the no first name index locations with original dataframe values
names_result[no_match_idx] = df.A.values[no_match_idx]
# make a dataframe using the results
df_out = pd.DataFrame(names_result, columns=['A'])
# to find names with a first and last name that are both found in the
# first names list:
# df_out['dups'] = df1.isin(name).sum(axis=1) > 1
answered Nov 21 '18 at 2:00
b2002b2002
546148
add a comment |
0
0
0
This method won't be fooled by a last name containing one of the first name strings, such as "Matten" or "Jakes", and will combine a first and last name if they are both found in the first names list, such as "Matt Henry" (shows "MattHenry" in the output dataframe).
# split the name strings into columns as new dataframe
df1 = df.A.str.split(' ', expand=True)
# Keep the first names in the new dataframe and fill the rest with
# empty strings, then sum the df1 column string values to make a new array
names_result = np.where(df1.isin(name), df1, '').sum(axis=1)
# find the array indexes where no first names were found
no_match_idx = np.where(names_result == '')[0]
# fill the no first name index locations with original dataframe values
names_result[no_match_idx] = df.A.values[no_match_idx]
# make a dataframe using the results
df_out = pd.DataFrame(names_result, columns=['A'])
# to find names with a first and last name that are both found in the
# first names list:
# df_out['dups'] = df1.isin(name).sum(axis=1) > 1
answered Nov 21 '18 at 2:00
b2002b2002
546148
This method won't be fooled by a last name containing one of the first name strings, such as "Matten" or "Jakes", and will combine a first and last name if they are both found in the first names list, such as "Matt Henry" (shows "MattHenry" in the output dataframe).
# split the name strings into columns as new dataframe
df1 = df.A.str.split(' ', expand=True)
# Keep the first names in the new dataframe and fill the rest with
# empty strings, then sum the df1 column string values to make a new array
names_result = np.where(df1.isin(name), df1, '').sum(axis=1)
# find the array indexes where no first names were found
no_match_idx = np.where(names_result == '')[0]
# fill the no first name index locations with original dataframe values
names_result[no_match_idx] = df.A.values[no_match_idx]
# make a dataframe using the results
df_out = pd.DataFrame(names_result, columns=['A'])
# to find names with a first and last name that are both found in the
# first names list:
# df_out['dups'] = df1.isin(name).sum(axis=1) > 1
answered Nov 21 '18 at 2:00
b2002b2002
546148
edited Nov 21 '18 at 2:38
answered Nov 21 '18 at 2:00
b2002b2002
546148
answered Nov 21 '18 at 2:00
b2002b2002
546148
answered Nov 21 '18 at 2:00
b2002b2002
546148
546148
add a comment |
add a comment |
draft saved
draft discarded
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
draft saved
draft discarded
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53386763%2fsplit-string-from-a-preset-list-of-strings-from-pandas-df-column%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
2
what if value of column A doesn't exist in list?
– AkshayNevrekar
Nov 20 '18 at 5:31
1
What about first names that aren't Jake,Matt,Henry ? Do you want to filter them out?
– CIsForCookies
Nov 20 '18 at 5:31
Then the original name should be retained. For example if the name is Dave Atkins then it should retain the name Dave Atkins but I have made sure that I have all the names. So that should not be a problem.
– Matt
Nov 20 '18 at 5:33