Here is the code which works fine:
import pandas as pd
# Create a Pandas dataframe from some data.
df = pd.DataFrame({'Data': [10, 20, 30, 20, 15, 30, 45]})
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('pandas_conditional.xlsx', engine='xlsxwriter')
# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1')
# Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets['Sheet1']
# Apply a conditional format to the cell range.
worksheet.conditional_format(1,1,1,1, {'type': '3_color_scale'}) ##CHANGES THE COLOR OF SECOND ROW
# Close the Pandas Excel writer and output the Excel file.
writer.save()
This creates below output.
My question is, Is it possible to include the Header Data in the pandas indexing? I want to start indexing from 1st row. So Header Data should have index 0. It is useful because in xlsxwriter 1st row has index 0.
Firstly index is an object and default index starts from 0. You can swift it by typing:
df.index += 1
As for the header's index name pandas method to_excel takes an argument which is called index_label. So your code should be:
import pandas as pd
# Create a Pandas dataframe from some data.
df = pd.DataFrame({'Data': [10, 20, 30, 20, 15, 30, 45]})
df.index += 1
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('pandas_conditional.xlsx', engine='xlsxwriter')
# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1', index_label='0')
# Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets['Sheet1']
# Apply a conditional format to the cell range.
worksheet.conditional_format(1,1,1,1, {'type': '3_color_scale'}) ##CHANGES THE COLOR OF SECOND ROW
# Close the Pandas Excel writer and output the Excel file.
writer.save()
Output:
Related
I have found a similar and well answered question, Python: Writing Images and dataframes to the same excel file, but the answer writes the image into the same sheet as the Dataframe. I have 5 images I want to write to separate worksheet to that of the Dataframe.
As this answer is well written I shall use it here if that is ok and ask how to write any 2 images to a separate worksheet in the created workbook?
Code
import pandas as pd
# Create a Pandas dataframe from some data.
df = pd.DataFrame({'Data': [10, 20, 30, 20, 15, 30, 45]})
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('pandas_image2.xlsx', engine='xlsxwriter')
# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1')
# Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets['Sheet2']
# Insert an image.
worksheet.insert_image('D3', 'TRAJ_FIG.PNG')
# Close the Pandas Excel writer and output the Excel file.
writer.save()
Desired result
An excel workbook with two sheets, the df written to one and 2 images written to the other worksheet.
Instead of using writer, add a new sheet using workbook.add_worksheet():
with pd.ExcelWriter('pandas_image2.xlsx', engine='xlsxwriter') as writer:
df.to_excel(writer, sheet_name='Sheet1')
workbook = writer.book
worksheet = workbook.add_worksheet('Sheet2')
worksheet.insert_image('D3', 'TRAJ_FIG.PNG')
I have a requirement where i want to append images to my excel sheet.
code to add 1 image:
import pandas as pd
## Create a Pandas dataframe from some data.
df = pd.DataFrame({'Data': [10, 20, 30, 20, 15, 30, 45]})
##Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('pandas_image.xlsx', engine='xlsxwriter')
## Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1')
## Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets['Sheet1']
## Insert an image.
worksheet.insert_image('D3', 'newImage.jpg')
## Close the Pandas Excel writer and output the Excel file.
writer.save()
#When I add 1 image to excel
**My requirement :**when I add new photos, it should get appended to my current data.
It should look like
You can find what I've tried so far below:
import pandas
from openpyxl import load_workbook
book = load_workbook('C:/Users/Abhijeet/Downloads/New Project/Masterfil.xlsx')
writer = pandas.ExcelWriter('C:/Users/Abhijeet/Downloads/New Project/Masterfiles.xlsx', engine='openpyxl',mode='a',if_sheet_exists='replace')
df.to_excel(writer,'b2b')
writer.save()
writer.close()
Generate Sample data
import pandas as pd
# dataframe Name and Age columns
df = pd.DataFrame({'Col1': ['A', 'B', 'C', 'D'],
'Col2': [10, 0, 30, 50]})
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('sample.xlsx', engine='xlsxwriter')
# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1', index=False)
# Close the Pandas Excel writer and output the Excel file.
writer.save()
This code will add two columns, Col1 and Col2, with data to Sheet1 of sample.xlsx.
To Append data to existing excel
import pandas as pd
from openpyxl import load_workbook
# new dataframe with same columns
df = pd.DataFrame({'Col1': ['E','F','G','H'],
'Col2': [100,70,40,60]})
writer = pd.ExcelWriter('sample.xlsx', engine='openpyxl')
# try to open an existing workbook
writer.book = load_workbook('sample.xlsx')
# copy existing sheets
writer.sheets = dict((ws.title, ws) for ws in writer.book.worksheets)
# read existing file
reader = pd.read_excel(r'sample.xlsx')
# write out the new sheet
df.to_excel(writer,index=False,header=False,startrow=len(reader)+1)
writer.close()
This code will append data at the end of an excel.
Check these as well
how to append data using openpyxl python to excel file from a specified row?
Suppose you have excel file abc.xlsx.
and You Have Dataframe to be appended as "df1"
1.Read File using Pandas
import pandas as pd
df = pd.read_csv("abc.xlsx")
2.Concat Two dataframes and write to 'abc.xlsx'
finaldf = pd.concat(df,df1)
# write finaldf to abc.xlsx and you are done
I'm running into an issue that I think relates to needing to:
export a dataframe to a new Excel worksheet (created at time of export)
write specific values to an existing sheet in same workbook
Doing both of the above in a loop
I can get 1 and 3 to work by themselves, and I can get 2 and 3 to work by themselves, but when I try to do all three things it doesn't work. I think there is some issue with the pandas to_excel using xlsxwriter engine conflicting with the sheets.write(row,column, value) to the same workbook.
For instance, this works by itself (note that I have the "writer" stuff to export dataframe to new sheet commented out):
import pandas as pd
import xlsxwriter
loopList = ["A","B","C","D","E"]
data = [['tom', 10], ['nick', 15], ['juli', 14]]
counter = 1
# Create the pandas DataFrame
df = pd.DataFrame(data, columns = ['Name', 'Age'])
workbook = xlsxwriter.Workbook('C:\\Test\\Test.xlsx')
totalsSheet = workbook.add_worksheet('Totals')
writer = pd.ExcelWriter('C:\\Test\\Test.xlsx', engine = 'xlsxwriter')
for sheets in loopList:
#df.to_excel(writer, sheet_name = sheets, index=False)
totalsSheet.write(counter, counter, sheets + str(counter))
counter+=1
#writer.save()
#writer.close()
workbook.close()
The above makes the test.xlsx workbook, with a Totals worksheet, with "A1", "B2", etc. in incrementing row/column.
Likewise, when I comment out the workbook stuff and UN comment the pandas-export dataframe to new sheets, that also works:
import pandas as pd
import xlsxwriter
loopList = ["A","B","C","D","E"]
data = [['tom', 10], ['nick', 15], ['juli', 14]]
counter = 1
# Create the pandas DataFrame
df = pd.DataFrame(data, columns = ['Name', 'Age'])
workbook = xlsxwriter.Workbook('C:\\Test\\Test.xlsx')
totalsSheet = workbook.add_worksheet('Totals')
writer = pd.ExcelWriter('C:\\Test\\Test.xlsx', engine = 'xlsxwriter')
for sheets in loopList:
df.to_excel(writer, sheet_name = sheets, index=False)
#totalsSheet.write(counter, counter, sheets + str(counter))
counter+=1
writer.save()
writer.close()
#workbook.close()
The above gives me a new Test workbook with 5 sheets (A, B, C, etc.) with the same dataframe exported to each.
However, I can't seem to do both; depending on the order in which I have the lines that write to Excel, it still only does one or the other (I don't get errors, I just get a result that's not both things I'm trying to do).
Is there a way to accomplish both of these things in the same loop?
I'm using python 3.x.x. Thanks for any help.
Could you not just run it in to separate loops that each open and close the file to ensure that it is available to each processes? Something like...
import pandas as pd
import xlsxwriter
loopList = ["A","B","C","D","E"]
data = [['tom', 10], ['nick', 15], ['juli', 14]]
counter = 1
# Create the pandas DataFrame
df = pd.DataFrame(data, columns = ['Name', 'Age'])
with pd.ExcelWriter('C:\\Test\\Test.xlsx', engine = 'xlsxwriter') as writer:
for sheets in loopList:
df.to_excel(writer, sheet_name = sheets, index=False)
workbook = xlsxwriter.Workbook('C:\\Test\\Test.xlsx')
totalsSheet = workbook.add_worksheet('Totals')
for sheets in loopList:
totalsSheet.write(counter, counter, sheets + str(counter))
counter+=1
workbook.close()
Update
Looking into it more, as the docs say xlsxwriter:
cannot read or modify existing Excel XLSX files.
So what you were trying before was causing the overwrite to happen. However, if you look into the docs more you will see that the key is to create the workbook object from the pd.ExcelWriter object. This will mean that both libraries can write to the file at the same time.
I installed xlsxwriter and the code below works for me:
import pandas as pd
import xlsxwriter
# data to write
loopList = ["A","B","C","D","E"]
data = [['tom', 10], ['nick', 15], ['juli', 14]]
# Create the pandas DataFrame
df = pd.DataFrame(data, columns = ['Name', 'Age'])
# create the writer object
writer = pd.ExcelWriter('Test.xlsx', engine='xlsxwriter')
# create the workbook object from the current writer object
# this means that pandas and xlsxwriter can both write to it
workbook = writer.book
totalsSheet = workbook.add_worksheet('Totals')
# set the counter
counter = 1
# lopo through and use xlsx writer to write specific cells
for sheets in loopList:
totalsSheet.write(counter, counter, sheets + str(counter))
counter+=1
# loop through generating new sheets and writing dfs to the file
for sheets in loopList:
df.to_excel(writer, sheet_name = sheets, index=False)
# save the written data
writer.save()
Im working on a project where I have to take excel file make changes to the data and save it
from pandas import ExcelWriter
import pandas as pd
dfs = pd.read_excel("infile.xlsx")
#manuplate data
writer = ExcelWriter('outfile.xlsx')
dfs.to_excel(writer,'Sheet5')
writer.save()
The problem I have is the newly saved excel file does not have the same format(cell widht, bold borders) as the input file. What can I do to solve this issue?
You can't preserve the formatting because pandas throws away all that information upon import. You would need to specify the formatting options you want in the output with the ExcelWriter object. If you use the option engine='xlsxwriter' you can then use all the xlsxwriter formatting options before writing the final file. You can find more details in the XlsxWriter documentation.
Example:
import pandas as pd
# This removes the default header style so we can override it later
import pandas.io.formats.excel
pandas.io.formats.excel.header_style = None
# Create a Pandas dataframe from some data.
df = pd.DataFrame({'Data1': [10, 20, 30, 20, 15, 30, 45],
'Data2': [90, 80, 30, 15, 88, 34, 41]})
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('pandas_conditional.xlsx', engine='xlsxwriter')
# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1')
# Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets['Sheet1']
# Create Format objects to apply to sheet
# https://xlsxwriter.readthedocs.io/format.html#format-methods-and-format-properties
red_bold = workbook.add_format({'bold': True, 'font_color': 'red'})
border = workbook.add_format({'border':5, 'border_color':'blue'})
#Apply formatting to sheet
worksheet.set_column('C:C', None, red_bold)
worksheet.set_column('A1:A8', None, border)
# Apply a conditional format to a cell range.
worksheet.conditional_format('B2:B8', {'type': '3_color_scale'})
# Close the Pandas Excel writer and output the Excel file.
writer.save()