I have dictionary of dataframes.
dd = {
'table': pd.DataFrame({'Name':['Banana'], 'color':['Yellow'], 'type':'Fruit'}),
'another_table':pd.DataFrame({'city':['Atlanta'],'state':['Georgia'], 'Country':['United States']}),
'and_another_table':pd.DataFrame({'firstname':['John'], 'middlename':['Patrick'], 'lastnme':['Snow']}),
}
I would like to create an Excel file which contains Excel Table objects created from these dataframes. Each Table needs to be on a separate Tab/Sheet and Table names should match dataframe names.
Is this possible to do with Python?
So far I was only able to export data to Excel normally without converting to tables using xlsxwriter
writer = pd.ExcelWriter('Results.xlsx', engine='xlsxwriter')
for sheet, frame in dd.items():
frame.to_excel(writer, sheet_name = sheet)
writer.save()
For writing multiple sheets from Pandas, use the openpyxl library. In addition, to prevent overwriting, set the workbook sheets before each update.
Try this code:
import pandas as pd
import openpyxl
dd = {
'table': pd.DataFrame({'Name':['Banana'], 'color':['Yellow'], 'type':'Fruit'}),
'another_table':pd.DataFrame({'city':['Atlanta'],'state':['Georgia'], 'Country':['United States']}),
'and_another_table':pd.DataFrame({'firstname':['John'], 'middlename':['Patrick'], 'lastnme':['Snow']}),
}
filename = 'Results.xlsx' # must exist
wb = openpyxl.load_workbook(filename)
writer = pd.ExcelWriter(filename, engine='openpyxl')
for sheet, frame in dd.items():
writer.sheets = dict((ws.title, ws) for ws in wb.worksheets) # need this to prevent overwrite
frame.to_excel(writer, index=False, sheet_name = sheet)
writer.save()
# convert data to tables
wb = openpyxl.load_workbook(filename)
for ws in wb.worksheets:
mxrow = ws.max_row
mxcol = ws.max_column
tab = openpyxl.worksheet.table.Table(displayName=ws.title, ref="A1:" + ws.cell(mxrow,mxcol).coordinate)
ws.add_table(tab)
wb.save(filename)
Output
Related
I am trying to create an excel file of 3 columns: System Date, Time, Value on a webpage at that time.
Intention is to create a dataframe of the 3 values, every time the code runs, and append the dataframe to existing excel workbook (with one existing sheet).
I am able to create dataframe every time code runs, but when I try to append it to an excel file, it throws error:
ValueError: Sheet 'Sheet1' already exists and if_sheet_exists is set to 'error'
Can you please suggest, where am I going wrong.
# Importing Libraries
from datetime import datetime
import pandas as pd
import requests
from bs4 import BeautifulSoup
import openpyxl
#getting today's date amd formatting it
now = datetime.now()
Date = now.strftime ("%d/%m/%Y")
Time = now.strftime ("%H:%M")
# GET request to scrape. 'Page' variable to assign contents
page = requests.get("https://www.traderscockpit.com/?pageView=live-nse-advance-decline-ratio-chart")
# Create BeautifulSoup object to parse content
soup = BeautifulSoup(page.content, 'html.parser')
adv = soup.select_one('a:-soup-contains("Advanced:")').next_sibling.strip()
dec = soup.select_one('a:-soup-contains("Declined:")').next_sibling.strip()
ADratio = round(int(adv)/int(dec), 2)
df = pd.DataFrame({tuple([Date, Time, ADratio])})
#Load workbook and read last used row
path = r'C:\Users\kashk\OneDrive\Documents\ADratios.xlsx'
writer = pd.ExcelWriter (path, engine='openpyxl', mode = 'a')
wb = openpyxl.load_workbook(path)
startrow = writer.sheets['Sheet1'].max_row
#Append data frame to existing table in existing sheet
df.to_excel (writer, sheet_name = 'Sheet1', index = False, header = False, startrow = startrow)
writer.save()
writer.close()
A fast and easy solution would be upgrading your pandas > 1.4.0 since it provides a if_sheet_exists = 'overlay' Source
pd.ExcelWriter(path, engine='openpyxl', mode='a', if_sheet_exists='overlay')
If you don't want to upgrade your pandas, there is a way to work around by removing and re-write the sheet into the excel file. (Not recommended if you have a lot of records since it will be slow).
path, sheet_name = 'ADratios.xlsx' , 'Sheet 1'
df.columns = ['Date','Time','ADratio']
with pd.ExcelWriter(path, engine='openpyxl', mode='a', if_sheet_exists='replace') as writer:
book = openpyxl.load_workbook(path, 'r')
df_bak = pd.read_excel(path)
writer.book = openpyxl.load_workbook(path)
writer.book.remove(writer.book.worksheets[writer.book.sheetnames.index(sheet_name)])
writer.sheets = {ws.title:ws for ws in writer.book.worksheets}
pd.concat([df_bak, df], axis=0).to_excel(writer, sheet_name=sheet_name, index = False)
I have a nested for loop that is taking data from a master file with multiple sheets and splits the data out by user for each sheet. I want to then write each users data to their own file with the same sheets as the master file.
Here is what I have so far:
tm_sheet_to_df_map = pd.read_excel(src_file_tm, sheet_name=None)
for key, value in sorted(tm_sheet_to_df_map.items(),reverse=True):
tm_group = value.groupby('TM')
for TM, group_df in tm_group:
attachment = attachment_path_tm / f'{TM}' / f'Q221 New Accounts - {TM}.xlsx'
attachment1 = os.makedirs(os.path.dirname(attachment), exist_ok=True)
writer = ExcelWriter(attachment, engine = 'xlsxwriter')
group_df.to_excel(writer, sheet_name =f'{key}', index=False)
writer.save()
PROBLEM - The above script creates a new file for each user, but will only write the final dataframe to each file, instead of adding all sheets from the master file. Any ideas how to write each sheet to the individual files? I've tried moving
writer.save() outside the loop with no luck.
You need an "append" mode for ExcelWriter:
try:
# append mode will fail if file does not exist
writer = ExcelWriter(attachment, engine = 'openpyxl', mode="a")
except FileNotFoundError:
writer = ExcelWriter(attachment, engine = 'openpyxl')
ExcelWriter docs
Hello I have data in list of dicts. I'm using panda DataFrame to parse from dict to excel. Data are fetch 5 different places. I would like to add data into different spreadsheet.
Here is the code I'm trying, but it doesn't add new sheets, it overwrites
def write_xlsx(filename, sheetname, data):
workbook = xlsxwriter.Workbook(filename)
checksheet = workbook.get_worksheet_by_name(sheetname)
if checksheet is None:
worksheet = workbook.add_worksheet(sheetname)
# Store the worksheet objects in a dict indexed by name.
my_worksheets = {}
for worksheet in workbook.worksheets():
my_worksheets[worksheet.get_name()] = worksheet
df = pd.DataFrame(data)
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter(filename, engine='xlsxwriter')
df.to_excel(writer, sheet_name=sheetname, index=False, startrow=1, header=False)
# Set the column widths
workbook = writer.book
worksheet = writer.sheets[sheetname]
header_format = workbook.add_format({'text_wrap': True})
columns_format = workbook.add_format({'text_wrap': True})
# Write the column headers with the defined format.
for col_num, value in enumerate(df.columns.values):
worksheet.write(0, col_num + 0, value, header_format)
writer.save()
As of now i can read EXCEL file's all sheet.
e.msgbox("select Excel File")
updated_deleted_xls = e.fileopenbox()
book = xlrd.open_workbook(updated_deleted_xls, formatting_info=True)
openfile = e.fileopenbox()
for sheet in book.sheets():
for row in range(sheet.nrows):
for col in range(sheet.ncols):
thecell = sheet.cell(row, 0)
xfx = sheet.cell_xf_index(row, 0)
xf = book.xf_list[xfx]
If you open your editor from the desktop or command line, you would have to specify the file path while trying to read the file:
import pandas as pd
df = pd.read_excel(r'File path', sheet_name='Sheet name')
Alternatively, if you open your editor in the file's directory, then you could read directly using the panda library
import pandas as pd
df = pd.read_excel('KPMG_VI_New_raw_data_update_final.xlsx', sheet_name='Title Sheet')
df1 = pd.read_excel('KPMG_VI_New_raw_data_update_final.xlsx',sheet_name='Transactions')
df2 = pd.read_excel('KPMG_VI_New_raw_data_update_final.xlsx', sheet_name='NewCustomerList')
df3 = pd.read_excel('KPMG_VI_New_raw_data_update_final.xlsx', sheet_name='CustomerDemographic')
df4 = pd.read_excel('KPMG_VI_New_raw_data_update_final.xlsx', sheet_name='CustomerAddress')
Maybe Pandaswould be helpful ( the go-to package for data) :
import pandas as pd
df = pd.read_excel('filname.xls', sheet = 0)
Edit: Since a lot of time has passed and pandas matured the arguemnts have change. So for pandas >1.0.0
import pandas as pd
df = pd.read_excel('filname.xls', sheet_name = 0)
You can use book.sheet_by_name() to read specific sheets by their name from xls file.
for name, sheet_name in zip(filename, sheetnumber):
book = xlrd.open_workbook(name)
sheet = book.sheet_by_name(sheet_name)
for row in range(sheet.nrows):
for column in range(sheet.ncols):
thecell = sheet.cell(row, 0)
xfx = sheet.cell_xf_index(row, 0)
xf = book.xf_list[xfx]
filename is the path to your xls file. Specify the sheet number you need to read in sheetnumber.
Alternatively, you could use book.sheet_by_index() and pass argument to return a specific sheet.
From docs:
sheet_by_index(sheetx)
Parameters: sheetx – Sheet index in range(nsheets)
For example:
first_sheet = book.sheet_by_index(0) # returns the first sheet.
You can use either book.sheet_by_name() or book.get_sheet()
Example using get_sheet()
book = xlrd.open_workbook(updated_deleted_xls, formatting_info=True)
sheet = book.get_sheet(0) #Gets the first sheet.
Example using sheet_by_name()
book = xlrd.open_workbook(updated_deleted_xls, formatting_info=True)
sheet_names = book.sheet_names()
xl_sheet = xl_workbook.sheet_by_name(sheet_names[0])
MoreInfo on getting sheet by sheet_by_name
can you teach me whether Python can write into a same Excel file, but 2 different spreadsheets (tabs)?
Just for example, I want to pick and write the titles of below 4 websites, and write them into the same file title.xls but respectively in its Sheet1 and Sheet 2.
www.dailynews.com
www.dailynews.co.zw
www.gulf-daily-news.com
www.dailynews.gov.bw
I do them in 2 scripts, each for 2 websites:
from bs4 import BeautifulSoup
import urllib2
import xlwt
line_in_list = ['www.dailynews.com','www.dailynews.co.zw']
# line_in_list = [www.gulf-daily-news.com','www.dailynews.gov.bw']
book = xlwt.Workbook(encoding='utf-8', style_compression = 0)
sheet = book.add_sheet('Sheet1', cell_overwrite_ok = True)
# sheet = book.add_sheet('Sheet2', cell_overwrite_ok = True)
for cor,websites in enumerate(line_in_list):
url = "http://" + websites
page = urllib2.urlopen(url)
soup = BeautifulSoup(page.read())
site_title = soup.find_all("title")
print site_title
sheet.write (cor, 0, site_title[0].text)
book.save("title.xls")
however, the script is overwriting the sheets. I can only have either Sheet1 or Sheet2 but never both.
any helps? thanks.
You can also do it using pandas.
import pandas as pd
# Add your data in list, which may contain a dictionary with the name of the
# columns as the key
df1 = pd.DataFrame({'website': ['www.dailynews.com', 'www.dailynews.co.zw']})
df2 = pd.DataFrame({'website': ['www.gulf-daily-news.com', 'www.dailynews.gov.bw']})
# Create a new excel workbook
writer = pd.ExcelWriter('title.xlsx', engine='xlsxwriter')
# Write each dataframe to a different worksheet.
df1.to_excel(writer, sheet_name='Sheet1')
df2.to_excel(writer, sheet_name='Sheet2')
# Save workbook
writer.close()
If I correctly understood what you need. Sorry, can't comment to make it more clear.
sheet1 = book.add_sheet('Sheet1', cell_overwrite_ok = True)
sheet2 = book.add_sheet('Sheet2', cell_overwrite_ok = True)
sheet1.write (cor, 0, site_title[0].text)
sheet2.write (cor, 0, site_title[0].text)
import numpy as np
import pandas as pd
# Create a Dataframe
df1 = pd.DataFrame(np.random.rand(100).reshape(50,2),columns=['a','b'])
df2 = pd.DataFrame(np.random.rand(100).reshape(50,2),columns=['a','b'])
# Excel path
excelpath = 'path_to_your_excel.xlsx'
# Write your dataframes to difference sheets
with pd.ExcelWriter(excelpath) as writer:
df1.to_excel(writer,sheet_name='Sheet1')
df2.to_excel(writer,sheet_name = 'Sheet2')
""" I noticed that the above script overwrite all existing columns of in
the excel. In case you want to keep some columns and sheet untouched,
you might consider doing it the following way"""
import pandas as pd
import numpy as np
from openpyxl import load_workbook
book = load_workbook(excelpath)
writer = pandas.ExcelWriter(excelpath, engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
df1.to_excel(writer, "Sheet1", columns=['a', 'b']) # only columns 'a' and 'b' will be populated
df2.to_excel(writer,"Sheet2",columns=['a','b']) # only columns 'a' and 'b' will be populated
writer.save()
--Append Excel Data Sheet to Spreadsheet
import pandas as pd
#import os
#from pandasql import sqldf
#pysqldf = lambda q: sqldf(q, globals())
df1 = pd.read_csv('MyData1.csv')
df2 = pd.read_csv('MyData2.csv')
print(df1)
print(df2)
Differences_df = df1.merge(df2, indicator=True, how='outer')
#Differences_df[merged['_merge'] == 'right_only']
print(Differences_df)
with pd.ExcelWriter('MyInputData.xlsx', mode='a') as writer:
Differences_df.to_excel(writer, sheet_name='Diff')
print("Spreadsheets Processed")