I imported a table form an excel that contains many sheets.
All the sheet needs to do the data wrangling.
I finished the data wrangling of the first five sheets, which are called data1, data2,data3, data4, data5.
I could export one of them(data1 to data5) to a CSV file. The problem is how can I export all of them into one CSV file with different sheets.
the codes I used are:
data3.to_csv('new.csv',index = False)
data2.to_csv('new.csv',index = False)
data1.to_csv('new.csv',index = False)
and so on.
But the original CSV file will be covered by the new one.
The short answer is that the CSV file format doesn't have any equivalent of sheets. You can either write the 5 sets to 5 separate csv files, or append them one after the other into a single file.
Related
I have excel file (.xlsx) with many sheets which contains many rows, columns, different column colors, size and so on... I just have to add some new rows(work with data not with as it called "conditional formatting"?).
I use pandas to import and save excel file. I'am also quite new to python.. I could not find the answer yet.
So my question is, is there any possibility to open excel file and update it with all its existing parameters like colors, font size and so on??
I'm trying to open and save it like:
my_excel_file = pd.read_excel(r'my_file.xlsx')
my_excel_file.to_excel('my_file.xlsx'), index = False)
all the sheets are gone, only one sheet saved, the same with colors, font size and so on.
From what it appears, you are opening one tab/sheet within Pandas and then saving that dataframe to a single sheet as well.
If you want to load all the data from the various tabs of your excel workbook, first load them and assign a name to them and thereafter save each of those dataframes to a specific tab in excel, for example:
import pandas as pd
df1 = pd.read_excel('file_name.xlsx', engine='openpyxl', sheet_name='tab1')
df2 = pd.read_excel('file_name.xlsx', engine='openpyxl', sheet_name='tab2')
Thereafter specify that you want to save these dataframes in different worksheets as opposed to overwriting the same sheet:
df1.to_excel('name_of_excel_file.xlsx', sheet_name='Sheet_name_1')
df2.to_excel('name_of_excel_file.xlsx', sheet_name='Sheet_name_2')
Perform as many times as need to - you can even create a function/loop to do it for you if it is repetitive.
This is my database:
https://archive.ics.uci.edu/ml/datasets/Parkinson+Speech+Dataset+with++Multiple+Types+of+Sound+Recordings
This database consist of training data and test data. The training data consists of many features; one column is one feature. I intend to convert each column into a separate Excel sheet.
The following is my Python code that I formulated to convert the entire text file into a CSV. But I intend to convert the entire text file into Excel sheets. For example, the entire text file contains 10 columns, so I want to create 10 Excel sheets with each column separated into one Excel sheet. Can any expert guide me on how to do it? I am completely new to Python so I hope someone can help me.
import pandas as pd
read_file = pd.read_csv (r'C://Users/RichardStone/Pycharm/Project/train_data.txt')
read_file.to_csv (r'C://Users/RichardStone/Pycharm/Project/train_data.csv', index=None)
Try this.
sheetnames = list()
for i in range(len(read_file.columns)):
sheetnames.append('Sheet' + str(i+1))
for i in range(len(read_file.columns)):
read_file.iloc[:, i].to_excel(sheetnames[i] + '.xlsx', index = False)
I am reading multiple tables values in one variable. I have all tables in list format.
I want each table to be written in different sheet if excel in csv format. I alread wrote on script which write all tables in csv, but here all tables are in same csv file, so distingushing each table become hard.
df = read_pdf("all_n.pdf", multiple_tables=True, pages="all")
#df contains multiple tables in list format
convert_into("all_n.pdf", "test.csv", output_format="csv", pages="all")
Each there any way so that I can write each table in df variable in different sheet of excel file?
Each
From Wikipedia:
In computing, a comma-separated values (CSV) file is a delimited text file that uses a comma to separate values. A CSV file stores tabular data (numbers and text) in plain text. Each line of the file is a data record. Each record consists of one or more fields, separated by commas. The use of the comma as a field separator is the source of the name for this file format.
CSV is not a format that can support multiple pages, since it stores the tabular data as plain text.
Is there is way to create sheet 2 in same csv file by using python code
yes. There is :
df = pd.read_excel("C:\\DWDM\\Status.xlsx") # read ur original file
workbook = load_workbook(filename="C:\\DWDM\\Status.xlsx")
ws2 = workbook.create_sheet("Summary", 0) # other sheet with name Summary is added to the same.
and you can check the same with "workbook.sheetnames"
You can do this by using multiple CSV files - one CSV file per sheet.
A comma-separated value file is a plain text format. It is only going to be able to represent flat data, such as a table (or a "sheet")
When storing multiple sheets, you should use separate CSV files. You can write each one separately and import/parse them individually into their destination.
Is there any way to create a CSV file with multiple sheets programmatically in Python?
Multiple CSV files. One CSV file per sheet.
A comma seperated value file is a plain text format. It is only going to be able to represent flat data, such as a table (or a 'Sheet')
For storing multiple sheets, you should use separate CSV files. You can write each one separately and import/parse them individually into their destination.
The xlsxwriter library is what you're looking for. It can make a workbook with multiple sheets.
Look at the link for tutorials and code.
P.S I am answering this because this is the first result I got when searching on how to do this. Hopefully this helps others.
Not sure what you are trying to do with Multiple Sheets of CSV's.
Let me elaborate my thinking on this.
Maybe you want a folder with different CSV files in it.
If you "can" use XML then probably you may want to have XML sheet in a big XML "Workbook".
Haven't seen multiple sheets of csv yet.
This worked for me as a conversion from excel to CSV while exporting individual sheet names.
xls = pd.read_excel/csv('file name.xls/csv', sheet_name =['1','2','3','4','5','6','7','8','9','10'])
#list out the sheets you want to export in the bracket above separated by commas and ' '
for sheet_name, df in xls.items():
df['sheets'] = sheet_name
df[['sheets']].to_csv(f'{sheet_name}.csv', header=None)
export_csv = df.to_csv (r'Location you want to export to on your machine',
index = None, header=True)