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Python - DocxTemplate - Not Printing "&" in final document

I am running a script that takes the names from a csv file and populates them into individual word documents from a template. I got that part. But here is where I need a bit of help.
Some cells in the csv file are two names, such as "Bobby & Sammy." When I go check the populated word document, it only has "Bobby Sammy." I know that the "&" is a special character, but I am not sure what I have to do for it to populate the word documents correctly.
Any and all help is appreciated.
Edit: Code
csvfn = "Addresses.csv"
df = pd.read_csv('Addresses.csv')
def mkw(n):
tpl = DocxTemplate('Envelope_Template.docx')
df_to_doct = df.to_dict()
x = df.to_dict(orient='records')
context = x
tpl.render(context[n])
tpl.save("%s.docx" %str(n))
wait = time.sleep(random.randint(1,3))
~
print ("There will be ", df2, "files")
~
for i in range(0, df2):
print("Making file: ",f"{i}," ,"..Please Wait...")
mkw(i)
print("Done! - Now check your files")
~ Denotes new cell, I am using JupyterLab
File is a standard csv file
Standard CSV File
Without "&" Prints fine
Empty space where "&" is supposed to be

Removing duplicate lines and split parallel corpus

I have parallel translated corpus in English-French (text.en,text.fr),
each text includes around 500K of lines (sentences in source and target languge). what I want is to:
1- Remove the duplicated lines in both texts using python command; and avoid any alignment problem in both files. e.g: command deleted line 32 in text.en, then of course delete it in text.fr.
2- Then Split both files into Train/Dev/Test data, only 1K for dev, and 1K for test, and the rest for train.
I need to split text.en and text.fr using the same command, so I could keep the alignment and corresponding sentences in both files.
It would be better if I could extract test and dev data randomly, that will help getting better results.
How can I do that? please write the commands.
I appreciate any help, Thank you !

If when you say lines you mean grammer sentences then you need to split sentences firstly by :-
Eng = "..."
Frn = "..."
GEngLines = Eng.split(".");
GFrnLines = Frn.split(".");
for i in range(len(GEngLines)):
for j in range(len(GFrnLines)):
if GEngLines[i] == GFrnLines[j] :
GEngLines.remove(i);
GFrnLines.remove(j);
DevLinesNumber = 500
TestLinesNumber = 500
EngDevLines = []
EngTestLines = []
EngTrainLines = []
FrnDevLines = []
FrnTestLines = []
FrnTrainLines = []
for i in range(len(GEngLines)):
if i < DevLinesNumber :
EngDevLines.append(GEngLines[i])
FrnDevLines.append(GFrnLines[i]);
elif i >= DevLinesNumber and i < DevLinesNumber + TestLinesNumber :
EngTestLines.append(GEngLines[i])
FrnTestLines.append(GFrnLines[i]);
else:
EngTrainLines.append(GEngLines[i])
FrnTrainLines.append(GFrnLines[i]);
But dont forget to add two tabs(4 spaces) before end two lines because i am useing mobile i couldnt write easily.

How to read a set of characters from a column, even though they are all different lengths? Python 3

my name is Rhein and I have just started to learn Python, and I'm having a lot of fun :D. I just finished a course on YouTube and I am currently working on a project of mine. Currently, I am trying to separate the columns into their own strings from a crime-data csv.
with open('C:/Users/aferdous/python-works/data-set/crime-data/crime_data-windows-1000.csv') as crime_data:
for crime in crime_data:
id = crime_data.readline(8) #<- prints the first x char of each line
print(id)
case_number = crime_data.readline(8) #<- prints the first x char of each line
print(case_number)
date = crime_data.readline(22) #<- prints the first x char of each line
print(date)
block = crime_data.readline(25) #<- prints the first x char of each line
print(block)
This was easy for the first two columns, since they all have the same amount of character lengths. But for 'block', the words in the columns have different lengths, so I do not know how to extract the right amount of characters from each word in each line. And there is a 1000 lines total.
- Thanks

I assumen that your csv format is "value1, value2, value3" if that the case you can user a python function called split. Examples:
...
columns = crime_data.split(",")
print(columns[0]) #print column 1
print(columns[2]) #print column 2
...
But for read csv in python there a lot better options you can search in google a examples I found:
https://gist.github.com/ultrakain/79758ff811f87dd11a8c6c80c28397c4
Reading a CSV file using Python

Trying to read text file and count words within defined groups

I'm a novice Python user. I'm trying to create a program that reads a text file and searches that text for certain words that are grouped (that I predefine by reading from csv). For example, if I wanted to create my own definition for "positive" containing the words "excited", "happy", and "optimistic", the csv would contain those terms. I know the below is messy - the txt file I am reading from contains 7 occurrences of the three "positive" tester words I read from the csv, yet the results print out to be 25. I think it's returning character count, not word count. Code:
import csv
import string
import re
from collections import Counter
remove = dict.fromkeys(map(ord, '\n' + string.punctuation))
# Read the .txt file to analyze.
with open("test.txt", "r") as f:
textanalysis = f.read()
textresult = textanalysis.lower().translate(remove).split()
# Read the CSV list of terms.
with open("positivetest.csv", "r") as senti_file:
reader = csv.reader(senti_file)
positivelist = list(reader)
# Convert term list into flat chain.
from itertools import chain
newposlist = list(chain.from_iterable(positivelist))
# Convert chain list into string.
posstring = ' '.join(str(e) for e in newposlist)
posstring2 = posstring.split(' ')
posstring3 = ', '.join('"{}"'.format(word) for word in posstring2)
# Count number of words as defined in list category
def positive(str):
counts = dict()
for word in posstring3:
if word in counts:
counts[word] += 1
else:
counts[word] = 1
total = sum (counts.values())
return total
# Print result; will write to CSV eventually
print ("Positive: ", positive(textresult))

I'm a beginner as well but I stumbled upon a process that might help. After you read in the file, split the text at every space, tab, and newline. In your case, I would keep all the words lowercase and include punctuation in your split call. Save this as an array and then parse it with some sort of loop to get the number of instances of each 'positive,' or other, word.
Look at this, specifically the "train" function:
https://github.com/G3Kappa/Adjustable-Markov-Chains/blob/master/markovchain.py
Also, this link, ignore the JSON stuff at the beginning, the article talks about sentiment analysis:
https://dev.to/rodolfoferro/sentiment-analysis-on-trumpss-tweets-using-python-
Same applies with this link:
http://adilmoujahid.com/posts/2014/07/twitter-analytics/
Good luck!

I looked at your code and passed through some of my own as a sample.
I have 2 idea's for you, based on what I think you may want.
First Assumption: You want a basic sentiment count?
Getting to 'textresult' is great. Then you did the same with the 'positive lexicon' - to [positivelist] which I thought would be the perfect action? Then you converted [positivelist] to essentially a big sentence.
Would you not just:
1. Pass a 'stop_words' list through [textresult]
2. merge the two dataframes [textresult (less stopwords) and positivelist] for common words - as in an 'inner join'
3. Then basically do your term frequency
4. It is much easier to aggregate the score then
Second assumption: you are focusing on "excited", "happy", and "optimistic"
and you are trying to isolate text themes into those 3 categories?
1. again stop at [textresult]
2. download the 'nrc' and/or 'syuzhet' emotional valence dictionaries
They breakdown emotive words by 8 emotional groups
So if you only want 3 of the 8 emotive groups (subset)
3. Process it like you did to get [positivelist]
4. do another join
Sorry, this is a bit hashed up, but if I was anywhere near what you were thinking let me know and we can make contact.
Second apology, Im also a novice python user, I am adapting what I use in R to python in the above (its not subtle either :) )

Using a dictionary as regex in Python

I had a Python question I was hoping for some help on.
Let's start with the important part, here is my current code:
import re #for regex
import numpy as np #for matrix
f1 = open('file-to-analyze.txt','r') #file to analyze
#convert files of words into arrays.
#These words are used to be matched against in the "file-to-analyze"
math = open('sample_math.txt','r')
matharray = list(math.read().split())
math.close()
logic = open('sample_logic.txt','r')
logicarray = list(logic.read().split())
logic.close()
priv = open ('sample_priv.txt','r')
privarray = list(priv.read().split())
priv.close()
... Read in 5 more files and make associated arrays
#convert arrays into dictionaries
math_dict = dict()
math_dict.update(dict.fromkeys(matharray,0))
logic_dict = dict()
logic_dict.update(dict.fromkeys(logicarray,1))
...Make more dictionaries from the arrays (8 total dictionaries - the same number as there are arrays)
#create big dictionary of all keys
word_set = dict(math_dict.items() + logic_dict.items() + priv_dict.items() ... )
statelist = list()
for line in f1:
for word in word_set:
for m in re.finditer(word, line):
print word.value()
The goal of the program is to take a large text file and perform analysis on it. Essentially, I want the program to loop through the text file and match words found in Python dictionaries and associate them with a category and keep track of it in a list.
So for example, let's say I was parsing through the file and I ran across the word "ADD". ADD is listed under the "math" or '0' category of words. The program should then add it to a list that it ran across a 0 category and then continue to parse the file. Essentially generating a large list that looks like [0,4,6,7,4,3,4,1,2,7,1,2,2,2,4...] with each of the numbers corresponding to a particular state or category of words as illustrated above. For the sake of understanding, we'll call this large list 'statelist'
As you can tell from my code, so far I can take as input the file to analyze, take and store the text files that contain the list of words into arrays and from there into dictionaries with their correct corresponding list value (a numerical value from 1 - 7). However, I'm having trouble with the analysis portion.
As you can tell from my code, I'm trying to go line by line through the text file and regex any of the found words with the dictionaries. This is done through a loop and regexing with an additional, 9th dictionary that is more or less a "super" dictionary to help simplify the parsing.
However, I'm having trouble matching all the words in the file and when I find the word, matching it to the dictionary value, not the key. That is when it runs across and "ADD" to add 0 to the list because it is a part of the 0 or "math" category.
Would someone be able to help me figure out how to write this script? I really appreciate it! Sorry for the long post, but the code requires a lot of explanation so you know what's going on. Thank you so much in advance for your help!

The simplest change to your existing code would just be to just keep track of both the word and the category in the loop:
for line in f1:
for word, category in word_set.iteritems():
for m in re.finditer(word, line):
print word, category
statelist.append(category)