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How can I show a specific word in a data set?

I just started to learn python. I have a question about matching some of the words in my dataset in excel.
words_list is included some of the words I would like to find in a dataset.
words_list = ('tried','mobile','abc')
df is the extract from excel and picked up a single column.
df =
0 to make it possible or easier for someone to do ...
1 unable to acquire a buffer item very likely ...
2 The organization has tried to make...
3 Broadway tried a variety of mobile Phone for the..
I would like to get the result like this:
'None',
'None',
'tried',
'tried','mobile'
I tried in Jupiter like this:
list = [ ]
for word in df:
if any (aa in word for aa in words_List):
list.append(word)
else:
list.append('None')
print(list)
But the result will show the whole sentence in df
'None'
'None'
'The organization has tried to make...'
'Broadway tried a variety of mobile Phone for the..'
Can I only show the result only in the words list?
Sorry for my English and
thank you all

I'd suggest a manipulation on the DataFrame (that should always be your first thought, use the power of pandas)
import pandas as pd
words_list = {'tried', 'mobile', 'abc'}
df = pd.DataFrame({'col': ['to make it possible or easier for someone to do',
'unable to acquire a buffer item very likely',
'The organization has tried to make',
'Broadway tried a variety of mobile Phone for the']})
df['matches'] = df['col'].str.split().apply(lambda x: set(x) & words_list)
print(df)
col matches
0 to make it possible or easier for someone to do {}
1 unable to acquire a buffer item very likely {}
2 The organization has tried to make {tried}
3 Broadway tried a variety of mobile Phone for the {mobile, tried}

The reason it's printing the whole line has to do with your:
for word in df:
Your "word" variable is actually taking the whole line. Then it's checking the whole line to see if it contains your search word. If it does find it, then it basically says, "yes, I found ____ in this line, so append the line to your list.
What it sounds like you want to do is first split the line into words, and THEN check.
list = [ ]
found = False
for line in df:
words = line.split(" ")
for word in word_list:
if word in words:
found = True
list.append(word)
# this is just to append "None" if nothing found
if found:
found = False
else:
list.append("None")
print(list)
As a side note, you may want to use pprint instead of print when working with lists. It prints lists, dictionaries, etc in easier to read layouts. I don't know if you'll need to install the package. That depends on how you initially installed python. But usage would be something like:
from pprint import pprint
dictionary = {'firstkey':'firstval','secondkey':'secondval','thirdkey':'thirdval'}
pprint(dictionary)

Highlight text in dataframe based on regex pattern

Problem: I have a use case wherein I'm required to highlight the word/words with red font color in a dataframe row based on a regex pattern. I landed upon a regex pattern as it ignores all spaces, punctuation, and case sensitivity.
Source: The original source comes from a csv file. So I'm looking to load it into a dataframe, do the pattern match highlight formatting and output it on excel.
Code: The code helps me with the count of words that match in the dataframe row.
import pandas as pd
import re
df = pd.read_csv("C:/filepath/filename.csv", engine='python')
p = r'(?i)(?<![^ .,?!-])Crust|good|selection|fresh|rubber|warmer|fries|great(?!-[^ .,?!;\r\n])'
df['Output'] = df['Output'].apply(lambda x: re.sub(p, red_fmt.format(r"\g<0>"), x))
Sample Data:
Input
Wow... Loved this place.
Crust is not good.
The selection on the menu was great and so were the prices.
Honeslty it didn't taste THAT fresh.
The potatoes were like rubber and you could tell they had been made up ahead of time being kept under a warmer.
The fries were great too.
Output: What I'm trying to achieve.

import re
# Console output color.
red_fmt = "\033[1;31m{}\033[0m"
s = """
Wow... Loved this place.
Crust is not good.
The selection on the menu was great and so were the prices.
Honeslty it didn't taste THAT fresh.
The potatoes were like rubber and you could tell they had been made up ahead of time being kept under a warmer.
The fries were great too.
"""
p = r'(?i)(?<![^ \r\n.,?!-])Crust|good|selection|fresh|rubber|warmer|fries|great(?!-[^ .,?!;\r\n])'
print(re.sub(p, red_fmt.format(r"\g<0>"), s))

Extracting #mentions from tweets using findall python (Giving incorrect results)

I have a csv file something like this
text
RT #CritCareMed: New Article: Male-Predominant Plasma Transfusion Strategy for Preventing Transfusion-Related Acute Lung Injury... htp://…
#CRISPR Inversion of CTCF Sites Alters Genome Topology & Enhancer/Promoter Function in #CellCellPress htp://.co/HrjDwbm7NN
RT #gvwilson: Where's the theory for software engineering? Behind a paywall, that's where. htp://.co/1t3TymiF3M #semat #fail
RT #sciencemagazine: What’s killing off the sea stars? htp://.co/J19FnigwM9 #ecology
RT #MHendr1cks: Eve Marder describes a horror that is familiar to worm connectome gazers. htp://.co/AEqc7NOWoR via #nucAmbiguous htp://…
I want to extract all the mentions (starting with '#') from the tweet text. So far I have done this
import pandas as pd
import re
mydata = pd.read_csv("C:/Users/file.csv")
X = mydata.ix[:,:]
X=X.iloc[:,:1] #I have multiple columns so I'm selecting the first column only that is 'text'
for i in range(X.shape[0]):
result = re.findall("(^|[^#\w])#(\w{1,25})", str(X.iloc[:i,:]))
print(result);
There are two problems here:
First: at str(X.iloc[:1,:]) it gives me ['CritCareMed'] which is not ok as it should give me ['CellCellPress'], and at str(X.iloc[:2,:]) it again gives me ['CritCareMed'] which is of course not fine again. The final result I'm getting is
[(' ', 'CritCareMed'), (' ', 'gvwilson'), (' ', 'sciencemagazine')]
It doesn't include the mentions in 2nd row and both two mentions in last row.
What I want should look something like this:
How can I achieve these results? this is just a sample data my original data has lots of tweets so is the approach ok?

You can use str.findall method to avoid the for loop, use negative look behind to replace (^|[^#\w]) which forms another capture group you don't need in your regex:
df['mention'] = df.text.str.findall(r'(?<![#\w])#(\w{1,25})').apply(','.join)
df
# text mention
#0 RT #CritCareMed: New Article: Male-Predominant... CritCareMed
#1 #CRISPR Inversion of CTCF Sites Alters Genome ... CellCellPress
#2 RT #gvwilson: Where's the theory for software ... gvwilson
#3 RT #sciencemagazine: What’s killing off the se... sciencemagazine
#4 RT #MHendr1cks: Eve Marder describes a horror ... MHendr1cks,nucAmbiguous
Also X.iloc[:i,:] gives back a data frame, so str(X.iloc[:i,:]) gives you the string representation of a data frame, which is very different from the element in the cell, to extract the actual string from the text column, you can use X.text.iloc[0], or a better way to iterate through a column, use iteritems:
import re
for index, s in df.text.iteritems():
result = re.findall("(?<![#\w])#(\w{1,25})", s)
print(','.join(result))
#CritCareMed
#CellCellPress
#gvwilson
#sciencemagazine
#MHendr1cks,nucAmbiguous

While you already have your answer, you could even try to optimize the whole import process like so:
import re, pandas as pd
rx = re.compile(r'#([^:\s]+)')
with open("test.txt") as fp:
dft = ([line, ",".join(rx.findall(line))] for line in fp.readlines())
df = pd.DataFrame(dft, columns = ['text', 'mention'])
print(df)
Which yields:
text mention
0 RT #CritCareMed: New Article: Male-Predominant... CritCareMed
1 #CRISPR Inversion of CTCF Sites Alters Genome ... CellCellPress
2 RT #gvwilson: Where's the theory for software ... gvwilson
3 RT #sciencemagazine: What’s killing off the se... sciencemagazine
4 RT #MHendr1cks: Eve Marder describes a horror ... MHendr1cks,nucAmbiguous
This might be a bit faster as you don't need to change the df once it's already constructed.

mydata['text'].str.findall(r'(?:(?<=\s)|(?<=^))#.*?(?=\s|$)')
Same as this: Extract hashtags from columns of a pandas dataframe, but for mentions.
#.*? carries out a non-greedy match for a word starting
with a hashtag
(?=\s|$) look-ahead for the end of the word or end of the sentence
(?:(?<=\s)|(?<=^)) look-behind to ensure there are no false positives if a # is used in the middle of a word
The regex lookbehind asserts that either a space or the start of the sentence must precede a # character.

How to return a word in a string if it starts with a certain character? (Python)

I'm building a reddit bot for practice that converts US dollars into other commonly used currencies, and I've managed to get the conversion part working fine, but now I'm a bit stuck trying to pass the characters that directly follow a dollar sign to the converter.
This is sort of how I want it to work:
def run_bot():
subreddit = r.get_subreddit("randomsubreddit")
comments = subreddit.get_comments(limit=25)
for comment in comments:
comment_text = comment.body
#If comment contains a string that starts with '$'
# Pass the rest of the 'word' to a variable
So for example, if it were going over a comment like this:
"I bought a boat for $5000 and it's awesome"
It would assign '5000' to a variable that I would then put through my converter
What would be the best way to do this?
(Hopefully that's enough information to go off, but if people are confused I'll add more)

You could use re.findall function.
>>> import re
>>> re.findall(r'\$(\d+)', "I bought a boat for $5000 and it's awesome")
['5000']
>>> re.findall(r'\$(\d+(?:\.\d+)?)', "I bought two boats for $5000 $5000.45")
['5000', '5000.45']
OR
>>> s = "I bought a boat for $5000 and it's awesome"
>>> [i[1:] for i in s.split() if i.startswith('$')]
['5000']

If you dealing with prices as in float number, you can use this:
import re
s = "I bought a boat for $5000 and it's awesome"
matches = re.findall("\$(\d*\.\d+|\d+)", s)
print(matches) # ['5000']
s2 = "I bought a boat for $5000.52 and it's awesome"
matches = re.findall("\$(\d*\.\d+|\d+)", s2)
print(matches) # ['5000.52']

Error: match word in file

There are two sentences in "test_tweet1.txt"
#francesco_con40 2nd worst QB. DEFINITELY Tony Romo. The man who likes to share the ball with everyone. Including the other team.
#mariakaykay aga tayo tomorrow ah. :) Good night, Ces. Love you! >:D<
In "Personal.txt"
The Game (rapper)
The Notorious B.I.G.
The Undertaker
Thor
Tiësto
Timbaland
T.I.
Tom Cruise
Tony Romo
Trajan
Triple H
My codes:
import re
popular_person = open('C:/Users/Personal.txt')
rpopular_person = popular_person.read()
file1 = open("C:/Users/test_tweet1.txt").readlines()
array = []
count1 = 0
for line in file1:
array.append(line)
count1 = count1 + 1
print "\n",count1, line
ltext1 = line.split(" ")
for i,text in enumerate(ltext1):
if text in rpopular_person:
print text
text2 = ' '.join(ltext1)
Results from the codes showed:
1 #francesco_con40 2nd worst QB. DEFINITELY Tony Romo. The man who likes to share the ball with everyone. Including the other team.
Tony
The
man
to
the
the
2 #mariakaykay aga tayo tomorrow ah. :) Good night, Ces. Love you! >:D<
aga
I tried to match word from "test_tweet1.txt" with "Personal.txt".
Expected result:
Tony
Romo
Any suggestion?

Your problem seems to be that rpopular_person is just a single string. Therefore, when you ask things like 'to' in rpopular_person, you get a value of True, because the characters 't', 'o' appear in sequence. I am assuming that the same goes for 'the' elsewhere in Personal.txt.
What you want to do is split up Personal.txt into individual words, the way you're splitting your tweets. You can also make the resulting list of words into a set, since that'll make your lookup much faster. Something like this:
people = set(popular_person.read().split())
It's also worth noticing that I'm calling split(), with no arguments. This splits on all whitespace--newlines, tabs, and so on. This way you get everything separately like you intend. Or, if you don't actually want this (since this will give you results of "The" all the time based on your edited contents of Personal.txt), make it:
people = set(popular_person.read().split('\n'))
This way you split on newlines, so you only look for full name matches.
You're not getting "Romo" because that's not a word in your tweet. The word in your tweet is "Romo." with a period. This is very likely to remain a problem for you, so what I would do is rearrange your logic (assuming speed isn't an issue). Rather than looking at each word in your tweet, look at each name in your Personal.txt file, and see if it's in your full tweet. This way you don't have to deal with punctuation and so on. Here's how I'd rewrite your functionality:
rpopular_person = set(personal.split())
with open("Personal.txt") as p:
people = p.read().split('\n') # Get full names rather than partial names
with open("test_tweet1.txt") as tweets:
for tweet in tweets:
for person in people:
if person in tweet:
print person

you need to split rpopular_person to get it to match words instead of substrings
rpopular_person = open('C:/Users/Personal.txt').read().split()
this gives:
Tony
The
the reason Romo isn't showing up is that on your line split you have "Romo." Maybe you should look for rpopular_person in the lines, instead of the other way around. Maybe something like this
popular_person = open('C:/Users/Personal.txt').read().split("\n")
file1 = open("C:/Users/test_tweet1.txt")
array = []
for count1, line in enumerate(file1):
print "\n", count1, line
for person in popular_person:
if person in line:
print person