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Inserting Data into an Excel file using Pandas - Python

I have an excel file that contains the names of 60 datasets.
I'm trying to write a piece of code that "enters" the Excel file, accesses a specific dataset (whose name is in the Excel file), gathers and analyses some data and finally, creates a new column in the Excel file and inserts the information gathered beforehand.
I can do most of it, except for the part of adding a new column and entering the data.
I was trying to do something like this:
path_data = **the path to the excel file**
recap = pd.read_excel(os.path.join(path_data,'My_Excel.xlsx')) # where I access the Excel file
recap['New information Column'] = Some Value
Is this a correct way of doing this? And if so, can someone suggest a better way (that works ehehe)
Thank you a lot!

You can import the excel file into python using pandas.
import pandas as pd
df = pd.read_excel (r'Path\Filename.xlsx')
print (df)
If you have many sheets, then you could do this:
import pandas as pd
df = pd.read_excel (r'Path\Filename.xlsx', sheet_name='sheetname')
print (df)
To add a new column you could do the following:
df['name of the new column'] = 'things to add'
Then when you're ready, you can export it as xlsx:
import openpyxl
# to excel
df.to_excel(r'Path\filename.xlsx')

Extracting individual rows from dataframe

I am currently doing one of my final assignment and I have a CSV file with a few columns of different data.
Currently interested in extracting out a single column and converting the individual rows into a txt file.
Here is my code:
import pandas as pd
import csv
df = pd.read_csv("AUS_NZ.csv")
print(df.head(10))
print(df["content"])
num_of_review = len(df["content"])
print(num_of_review)
for i in range (num_of_review):
with open ("{}.txt".format(i),"a", encoding="utf-8") as f:
f.write(df["content"][i])
No issue with extracting out the individual rows. But when I examine the txt files that was extracted and look at the content, I noticed that it copied out the text (which is what I want) but it did so twice (which is not what I want).
Example:
"This is an example of what the dataframe have at that particular column which I want to convert to a txt file."
This is what was copied to the txt file:
"This is an example of what the dataframe have at that particular column which I want to convert to a txt file.This is an example of what the dataframe have at that particular column which I want to convert to a txt file."
Any advise on how to just copy the content once only?

Thanks! While thinking about how to rectify this, I came to the same conclusion as you. I made a switch from "a" to "w" and it solved that issue.
Too used to append so I tried that before I tried write.
The correct code:
import pandas as pd
import csv
df = pd.read_csv("AUS_NZ.csv")
print(df.head(10))
print(df["content"])
num_of_review = len(df["content"])
print(num_of_review)
for i in range (num_of_review):
with open ("{}.txt".format(i),"w", encoding="utf-8") as f:
f.write(df["content"][i])

a way to update csv file without rewriting

import pandas as pd
import csv,sched,nltk,arrow
from time import perf_counter
def ngram_search():
#code here
item['length']=len(word_tokenize(s)) # number
item['time edit']=arrow.utcnow().shift(hours=-1).humanize().upper() # text
item['top1'] = "word"
return item
path=r"C:\Users\Sublime Text\products.csv"
df = pd.read_csv(path)
saved_column = df['Name of Product']
for i in saved_column:
name=i.replace(",","+").replace(";","+")
item=ngram_search(name)
#update csv file here add the columns of items to the csv file
I am trying to add to an existing csv file (15 columns, 283216 row), the function returns a dictionary of 3 values.
Is there a way to directly update the csv file without rewriting it?

DataFrame.to_csv() has option mode="a" to append to existing file.
You have to only write the same number of columns and write them in the same order (with the same separator, etc.) to create correctly formatted CVS.
This way you can only append to the end of the file. If you need to write between existing rows or add a new column then you have to read all. OR you have to read from one file and write to a new one (all data with changes).

Parsing and saving the rows of excel file using pandas

Have an excel file with a column with some text in each row of this column.
I'm using pandas pd.read_excel() to open this .xlsx file. Then I would like to do the following: I would like to save every row of this column as a distinct .txt file (that would have the text from this row inside this file). Is it possible to be done via pandas?

the basic idea would be to use an iterator to loop over the rows, opening a each file and writing the value in, something like:
import pandas as pd
df = pd.read_excel('test.xlsx')
for i, value in enumerate(df['column']):
with open(f'row-{i}.txt', 'w') as fd:
fd.write(value)

How to save the changes I made on an Excel sheet?

I read an Excel Sheet this way :
import pandas as pd
xl = pd.ExcelFile("Path\file_name.xlsx")
xl.parse("Sheet_name")
and now I make some changes, for example I fill all null values with string "NA"
df = df.fillna("NA")
now I wish to write back the changes to the original Excel file...

You could simply write the changed data to the existing file using to_excel:
df.to_excel("Path\file_name.xlsx", "Sheet_name")

I would work with CSV files if you have large data sets.
save excel as .csv
data = pd.read_csv('name.csv')
data.to_csv('name.csv')