I am newbee to JSON and python programming and I am looking for some help in converting below json data from Spotify related artist information to be able to load into excel or csv file.
Expected output columns:
expected output columns
JSON related artist information
you can use pandas in this case. here's an example
import pandas
pandas.read_json("spotify.json").to_excel("spotify.xlsx")
basically you need to install pandas first with this command
pip install pandas
then you can use it right away as i suggested. remember to put up the file in the same directory if you dont want to use path and change your current working directory like this
import os
path = os.path.abspath(os.path.dirname(sys.argv[0]))
os.chdir(path)
Related
I am writing a cleaning function to clean my excel files to analyse them. I get a excel sheet everyday which is named for example:
"tourniquets_27.07.2022_raw.xls"
I get such a sheet everyday and so the date changes to that day. I now change the dates manually but I would love to make this automatic. I also save the file as follow: "tourniquets_28.07.2022_cleaned.xls". The dates need to bne changed here as well.
I tried the following code but it gives an error, I tried other things as well but this seems to be the most close to what I want.
import pandas as pd
import os
from pathlib import Path
from datetime import date
#assuming the files are in the directory:
folder = Path("C:/Users/JHA4/Desktop/Code/Tourniquets/Cleaned")
date_string = f"tourniquets_{date.today().month}.{date.today().day}.{date.today().year}_raw.xlsx"
xlsx_file = folder.glob(date_string)
#read in data
df = pd.read_excel(io=next(xlsx_file)
#Save it back to excel with a new name=
df.to_excel(io=next(xlsx_file))
Hope that I asked everything clearly!
Thank you in advance.
I'm trying to create a dataframe using a csv file for an assignment however, every time I would run my program it would show me an error that the file couldn't be found. My code is the following:
import pandas as pd
df = pd.read_csv('thefile')
The code returns an error no matter where I place my file. When I checked for the path using the code below:
import os
print(os.getcwd())
It showed me that the path is correct and it is looking inside the folder where my csv file is located but it still returns me the same error.
When reading in files, the 'thefile' must be followed by a .csv extension in the reference, as follows; 'thefile.csv'.
You need to add .csv behind the thefile,
without it, it doesn't know which file to look for it could be thefile.txt, thefile.conf, thefile.csv, thefile.....
So your code should look like this.
import pandas as pd
df = pd.read_csv('thefile.csv')
(Very new coder, first time here, apologies if there are errors in writing)
I have a csv file I made from Excel called SouthKoreaRoads.csv and I'm supposed to read that csv file using Pandas. Below is what I used:
import pandas as pd
import os
SouthKoreaRoads = pd.read_csv("SouthKoreaRoads.csv")
I get a FileNotFoundError, and I'm really new and unsure how to approach this. Could anyone help, give advice, or anything? Many thanks in advance
just some explanation aside. Before you can use pd.read_csv to import your data, you need to locate your data in your filesystem.
Asuming you use a jupyter notebook or pyton file and the csv-file is in the same directory you are currently working in, you just can use:
import pandas as pd SouthKoreaRoads_df = pd.read_csv('SouthKoreaRoads.csv')
If the file is located in another directy, you need to specify this directory. For example if the csv is in a subdirectry (in respect to the python / jupyter you are working on) you need to add the directories name. If its in folder "data" then add data in front of the file seperated with a "/"
import pandas as pd SouthKoreaRoads_df = pd.read_csv('data/SouthKoreaRoads.csv')
Pandas accepts every valid string path and URLs, thereby you could also give a full path.
import pandas as pd SouthKoreaRoads_df = pd.read_csv('C:\Users\Ron\Desktop\Clients.csv')
so until now no OS-package needed. Pandas read_csv can also pass OS-Path-like-Objects but the use of OS is only needed if you want specify a path in a variable before accessing it or if you do complex path handling, maybe because the code you are working on needs to run in a nother environment like a webapp where the path is relative and could change if deployed differently.
please see also:
https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html
https://docs.python.org/3/library/os.path.html
BR
SouthKoreaRoads = pd.read_csv("./SouthKoreaRoads.csv")
Try this and see whether it could help!
Try to put the full path, like "C:/users/....".
I have following N number of invoice data in Excel and I want to create CSV of that file so that it can be imported whenever needed...so how can I archive this?
Here is a screenshot:
Assuming you have a Folder "excel" full of Excel Files within your Project-Directory and you also have another folder "csv" where you intend to put your generated CSV Files, you could pretty much easily batch-convert all the Excel Files in the "excel" Directory into "csv" using Pandas.
It will be assumed that you already have Pandas installed on your System. Otherwise, you could do that via: pip install pandas. The fairly commented Snippet below illustrates the Process:
# IMPORT DATAFRAME FROM PANDAS AS WELL AS PANDAS ITSELF
from pandas import DataFrame
import pandas as pd
import os
# OUR GOAL IS:::
# LOOP THROUGH THE FOLDER: excelDir.....
# AT EACH ITERATION IN THE LOOP, CHECK IF THE CURRENT FILE IS AN EXCEL FILE,
# IF IT IS, SIMPLY CONVERT IT TO CSV AND SAVE IT:
for fileName in os.listdir(excelDir):
#DO WE HAVE AN EXCEL FILE?
if fileName.endswith(".xls") or fileName.endswith(".xlsx"):
#IF WE DO; THEN WE DO THE CONVERSION USING PANDAS...
targetXLFile = os.path.join(excelDir, fileName)
targetCSVFile = os.path.join(csvDir, fileName) + ".csv"
# NOW, WE READ "IN" THE EXCEL FILE
dFrame = pd.read_excel(targetXLFile)
# ONCE WE DONE READING, WE CAN SIMPLY SAVE THE DATA TO CSV
pd.DataFrame.to_csv(dFrame, path_or_buf=targetCSVFile)
Hope this does the Trick for you.....
Cheers and Good-Luck.
Instead of putting total output into one csv, you could go with following steps.
Convert your excel content to csv files or csv-objects.
Each object will be tagged with invoice id and save into dictionary.
your dictionary data structure could be like {'invoice-id':
csv-object, 'invoice-id2': csv-object2, ...}
write custom function which can reads your csv-object, and gives you
name,product-id, qty, etc...
Hope this helps.
I'm generating an csv file that is opened by excel and converted to xlsx manually.
The csv contains some path to .txt files.
Is it possible to build the file path in such way that when the csv is converted to xlsx , they became clickable hyperlinks ?
Thanks.
I would be interested to understand your workflow a bit better, but to try and help with your specific request:
The HYPERLINK solution proposed in the comments looks like a good one
If you are able to implement that upstream in the csv generation step then great
If not and/or you are interested in automating the conversion process, consider using the pandas library:
Create a DataFrame object from a csv using the pandas.read_csv method
Convert your paths to HYPERLINKs
Write back to xlsx using the pandas.DataFrame.to_excel method
E.g. if you have a file original.csv and the relevant column header is file_paths:
import pandas as pd
df = pd.read_csv('original.csv')
df['file_paths'] = '=HYPERLINK("' + df['file_paths'] + '")'
df.to_excel('new.xlsx', index=False)
Hope that helps!
Jon