While making my bot to set permissions automatically while it came into a guild, Writing codes for this seemed getting too long. So, I just wanted to made my bot to get xlsx file as dataframe and set permissions from that data inside.
I wanted to make this xlsx file of mine as multiple-columned dataframe, but I don't think my program recognises it as one. Do I have my errors in my code below or I have to change my excel file for it to be rocognised as I wanted?
from pandas import read_excel
perm_data = read_excel('E:/Discord bot/Grail-Relique/data/xlsx/TextPermission.xlsx', header=[0,1], engine='openpyxl')
print(perm_data)
print(perm_data.loc[0,(0,0)])
result
This should do the work:
import pandas as pd
df = pd.read_excel('your/path/to/file.xlsx',
header=[0,1],
index_col=0)
print(df.head())
Related
I have a Python script which loads an .xslx file into a pandas dataframe using read_excel:
import os
import pandas as pd
V_file = "My_file.xlsx"
V_path = r"C:\My_folder"
os.chdir(V_path)
V_df = pd.read_excel(V_file, sheet_name = "Sheet1")
This works for files saved locally. However, I want to read in a file that is saved in Sharepoint. Does anyone know how I can adapt the code above to do this please? And also, if it's not too much trouble, an explanation of what the adapted code is doing exactly please?
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')
I am dealing with a certain .asc file format which contains some data regarding weight and height. I just want to find BMI indexes of people with this data. I am not able to make sense of the dataframe formed after reading the data.
import pandas as pd
df = pd.read_table("data.asc")
I am not able to make sense of the result that I get. Please help me out
I recently had to work with a file with the extension "asc". My solution was the following:
I opened the file with a text editor and check the separator for the file, then transform it into a spreadsheet. In my case, I turned the document into a "csv" file.
After that I ran:
import pandas as pd
df = pd.read_csv('path to your file')
I'm trying to read binary Excel files using read_excel method in pandas with pyxlsb engine as below:
import pandas as pd
df = pd.read_excel('test.xlsb', engine='pyxlsb')
If the xlsb file is like this file (Right now, I'm sharing this file via WeTransfer, but if there is a better way to share files on StackOverflow, let me know), the returned dataframe is filled with NaN's. I suspected that it might be because the file was saved with active cell pointing at the empty cells after the data originally. So I tried this:
import pandas as pd
with open('test.xlsb', 'rb') as data:
data.seek(0,0)
df = pd.read_excel(data, engine='pyxlsb')
but it still doesn't seem to work. I also tried reading the data from byte number 0 (from the beginning), writing it into a new file, 'test_1.xlsb', and finally reading it with pandas, but that doesn't work.
with open('test.xlsb','rb') as data:
data.seek(0,0)
with open('test_1.xlsb','wb') as outfile:
outfile.write(data.read())
df = pd.read_excel('test_1.xlsb', engine='pyxlsb')
If anyone has suggestion as to what might be going on and how to resolve it, I'd greatly appreciate the help.
I am trying to restructure the way my precipitations' data is being organized in an excel file. To do this, I've written the following code:
import pandas as pd
df = pd.read_excel('El Jem_Souassi.xlsx', sheetname=None, header=None)
data=df["El Jem"]
T=[]
for column in range(1,56):
liste=data[column].tolist()
for row in range(1,len(liste)):
liste[row]=str(liste[row])
if liste[row]!='nan':
T.append(liste[row])
result=pd.DataFrame(T)
result
This code works fine and through Jupyter I can see that the result is good
screenshot
However, I am facing a problem when attempting to save this dataframe to a csv file.
result.to_csv("output.csv")
The resulting file contains the vertical index column and it seems I am unable to call for a specific cell.
(Hopefully, someone can help me with this problem)
Many thanks !!
It's all in the docs.
You are interested in skipping the index column, so do:
result.to_csv("output.csv", index=False)
If you also want to skip the header add:
result.to_csv("output.csv", index=False, header=False)
I don't know how your input data looks like (it is a good idea to make it available in your question). But note that currently you can obtain the same results just by doing:
import pandas as pd
df = pd.DataFrame([0]*16)
df.to_csv('results.csv', index=False, header=False)