I create a excel file from a dataframe:
#writer = pd.ExcelWriter('ΜΟΝΑΔΙΚΕΣ_ΠΡΟΣΛΗΨΕΙΣ.xlsx', engine='xlsxwriter')
#uniq_pros.to_excel(writer, sheet_name='Sheet1')
#writer.save()
how can add a watermark in every page of excel file?
or
a header with logo text and image in every first row of pages (or 25lines?)
with python
The usual way to add a watermark in Excel (as suggested by Microsoft) is to add an image to the header. Here is one way to do it via Pandas and XlsxWriter:
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('test.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']
# Set a worksheet header with image.
worksheet.set_header('&C&[Picture]',
{'image_center': 'watermark.png'})
# Close the Pandas Excel writer and output the Excel file.
writer.save()
Output:
See also Example: Adding Headers and Footers to Worksheets in the XlsxWriter docs.
I am storing a pandas DataFrame in an Excel sheet. When I re-run my code, I want the sheet completely overwritten. This is important because my code writes to the same file a few different times, i.e., loading and saving certain sheets at different moments, not wanting to disturb the sheets not currently being changed. Because of this, if a new iteration of the code produces fewer rows or columns, the old data will still be there. For example, if iteration #1 produces 500 rows but iteration #2 only produces 499, that 500th row will still show up in my Excel file.
I'm aware I could loop through all the cells and set their values to None, but I thought it would be more efficient to remove a given sheet completely, create_sheet with the same sheet name, and then save my DataFrame to the new sheet. The code below is a MRE of what I'm trying to do. It successfully removes the sheet, creates a new one, and saves the file, but the to_excel doesn't seem to be executing. The resulting Excel file has the 'test' sheet, but it is blank.
import pandas as pd
import numpy as np
import openpyxl
from openpyxl import load_workbook
from openpyxl import Workbook
df_data = {'A': np.random.randint(1, 50, 20),
'B': np.random.randint(1, 50, 20),
'C': np.random.randint(1, 50, 20),
'D': np.random.randint(1, 50, 20)}
df = pd.DataFrame(data=df_data)
fn = 'test.xlsx'
sheet = 'test'
df.to_excel(fn, sheet_name=sheet)
df2 = pd.read_excel(fn, sheet_name=sheet, index_col=0)
df2.drop(columns=['A'], inplace=True)
book = load_workbook(fn)
writer = pd.ExcelWriter(fn, engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
s = book[sheet]
book.remove(s)
book.create_sheet(sheet, 0)
#THIS CODE WILL ACTUALLY WRITE TO THE SHEET, BUT df2 WILL NOT
#s2 = book[sheet]
#s2['A1'] = 'This will write to the sheet'
df2.to_excel(writer, sheet_name=sheet)
writer.save()
Note that my commented code will write to the proper sheet if uncommented. It seems to just be the to_excel line that doesn't work.
You could do this by using a function:
import pandas as pd
def write2excel(filename,sheetname,dataframe):
with pd.ExcelWriter(filename, engine='openpyxl', mode='a') as writer:
workBook = writer.book
try:
workBook.remove(workBook[sheetname])
except:
print("There is no such sheet in this file")
finally:
dataframe.to_excel(writer, sheet_name=sheetname,index=False)
writer.save()
After this, assuming you have a datafram df, A workbook Myfile.xlsx and the sheet you want to overwrite THE_sheet do
write2excel('Myfile.xlsx','THE_sheet',df)
I want to use excel files to store data elaborated with python. My problem is that I can't add sheets to an existing excel file. Here I suggest a sample code to work with in order to reach this issue
import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
x1 = np.random.randn(100, 2)
df1 = pd.DataFrame(x1)
x2 = np.random.randn(100, 2)
df2 = pd.DataFrame(x2)
writer = pd.ExcelWriter(path, engine = 'xlsxwriter')
df1.to_excel(writer, sheet_name = 'x1')
df2.to_excel(writer, sheet_name = 'x2')
writer.save()
writer.close()
This code saves two DataFrames to two sheets, named "x1" and "x2" respectively. If I create two new DataFrames and try to use the same code to add two new sheets, 'x3' and 'x4', the original data is lost.
import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
x3 = np.random.randn(100, 2)
df3 = pd.DataFrame(x3)
x4 = np.random.randn(100, 2)
df4 = pd.DataFrame(x4)
writer = pd.ExcelWriter(path, engine = 'xlsxwriter')
df3.to_excel(writer, sheet_name = 'x3')
df4.to_excel(writer, sheet_name = 'x4')
writer.save()
writer.close()
I want an excel file with four sheets: 'x1', 'x2', 'x3', 'x4'.
I know that 'xlsxwriter' is not the only "engine", there is 'openpyxl'. I also saw there are already other people that have written about this issue, but still I can't understand how to do that.
Here a code taken from this link
import pandas
from openpyxl import load_workbook
book = load_workbook('Masterfile.xlsx')
writer = pandas.ExcelWriter('Masterfile.xlsx', engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])
writer.save()
They say that it works, but it is hard to figure out how. I don't understand what "ws.title", "ws", and "dict" are in this context.
Which is the best way to save "x1" and "x2", then close the file, open it again and add "x3" and "x4"?
Thank you. I believe that a complete example could be good for anyone else who have the same issue:
import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
x1 = np.random.randn(100, 2)
df1 = pd.DataFrame(x1)
x2 = np.random.randn(100, 2)
df2 = pd.DataFrame(x2)
writer = pd.ExcelWriter(path, engine = 'xlsxwriter')
df1.to_excel(writer, sheet_name = 'x1')
df2.to_excel(writer, sheet_name = 'x2')
writer.close()
Here I generate an excel file, from my understanding it does not really matter whether it is generated via the "xslxwriter" or the "openpyxl" engine.
When I want to write without loosing the original data then
import pandas as pd
import numpy as np
from openpyxl import load_workbook
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
book = load_workbook(path)
writer = pd.ExcelWriter(path, engine = 'openpyxl')
writer.book = book
x3 = np.random.randn(100, 2)
df3 = pd.DataFrame(x3)
x4 = np.random.randn(100, 2)
df4 = pd.DataFrame(x4)
df3.to_excel(writer, sheet_name = 'x3')
df4.to_excel(writer, sheet_name = 'x4')
writer.close()
this code do the job!
For creating a new file
x1 = np.random.randn(100, 2)
df1 = pd.DataFrame(x1)
with pd.ExcelWriter('sample.xlsx') as writer:
df1.to_excel(writer, sheet_name='x1')
For appending to the file, use the argument mode='a' in pd.ExcelWriter.
x2 = np.random.randn(100, 2)
df2 = pd.DataFrame(x2)
with pd.ExcelWriter('sample.xlsx', engine='openpyxl', mode='a') as writer:
df2.to_excel(writer, sheet_name='x2')
Default is mode ='w'.
See documentation.
In the example you shared you are loading the existing file into book and setting the writer.book value to be book. In the line writer.sheets = dict((ws.title, ws) for ws in book.worksheets) you are accessing each sheet in the workbook as ws. The sheet title is then ws so you are creating a dictionary of {sheet_titles: sheet} key, value pairs. This dictionary is then set to writer.sheets. Essentially these steps are just loading the existing data from 'Masterfile.xlsx' and populating your writer with them.
Now let's say you already have a file with x1 and x2 as sheets. You can use the example code to load the file and then could do something like this to add x3 and x4.
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
writer = pd.ExcelWriter(path, engine='openpyxl')
df3.to_excel(writer, 'x3', index=False)
df4.to_excel(writer, 'x4', index=False)
writer.save()
That should do what you are looking for.
A simple example for writing multiple data to excel at a time. And also when you want to append data to a sheet on a written excel file (closed excel file).
When it is your first time writing to an excel. (Writing "df1" and "df2" to "1st_sheet" and "2nd_sheet")
import pandas as pd
from openpyxl import load_workbook
df1 = pd.DataFrame([[1],[1]], columns=['a'])
df2 = pd.DataFrame([[2],[2]], columns=['b'])
df3 = pd.DataFrame([[3],[3]], columns=['c'])
excel_dir = "my/excel/dir"
with pd.ExcelWriter(excel_dir, engine='xlsxwriter') as writer:
df1.to_excel(writer, '1st_sheet')
df2.to_excel(writer, '2nd_sheet')
writer.save()
After you close your excel, but you wish to "append" data on the same excel file but another sheet, let's say "df3" to sheet name "3rd_sheet".
book = load_workbook(excel_dir)
with pd.ExcelWriter(excel_dir, engine='openpyxl') as writer:
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
## Your dataframe to append.
df3.to_excel(writer, '3rd_sheet')
writer.save()
Be noted that excel format must not be xls, you may use xlsx one.
Every time you want to save a Pandas DataFrame to an Excel, you may call this function:
import os
def save_excel_sheet(df, filepath, sheetname, index=False):
# Create file if it does not exist
if not os.path.exists(filepath):
df.to_excel(filepath, sheet_name=sheetname, index=index)
# Otherwise, add a sheet. Overwrite if there exists one with the same name.
else:
with pd.ExcelWriter(filepath, engine='openpyxl', if_sheet_exists='replace', mode='a') as writer:
df.to_excel(writer, sheet_name=sheetname, index=index)
I would strongly recommend you work directly with openpyxl since it now supports Pandas DataFrames.
This allows you to concentrate on the relevant Excel and Pandas code.
Can do it without using ExcelWriter, using tools in openpyxl
This can make adding fonts to the new sheet much easier using openpyxl.styles
import pandas as pd
from openpyxl import load_workbook
from openpyxl.utils.dataframe import dataframe_to_rows
#Location of original excel sheet
fileLocation =r'C:\workspace\data.xlsx'
#Location of new file which can be the same as original file
writeLocation=r'C:\workspace\dataNew.xlsx'
data = {'Name':['Tom','Paul','Jeremy'],'Age':[32,43,34],'Salary':[20000,34000,32000]}
#The dataframe you want to add
df = pd.DataFrame(data)
#Load existing sheet as it is
book = load_workbook(fileLocation)
#create a new sheet
sheet = book.create_sheet("Sheet Name")
#Load dataframe into new sheet
for row in dataframe_to_rows(df, index=False, header=True):
sheet.append(row)
#Save the modified excel at desired location
book.save(writeLocation)
You can read existing sheets of your interests, for example, 'x1', 'x2', into memory and 'write' them back prior to adding more new sheets (keep in mind that sheets in a file and sheets in memory are two different things, if you don't read them, they will be lost). This approach uses 'xlsxwriter' only, no openpyxl involved.
import pandas as pd
import numpy as np
path = r"C:\Users\fedel\Desktop\excelData\PhD_data.xlsx"
# begin <== read selected sheets and write them back
df1 = pd.read_excel(path, sheet_name='x1', index_col=0) # or sheet_name=0
df2 = pd.read_excel(path, sheet_name='x2', index_col=0) # or sheet_name=1
writer = pd.ExcelWriter(path, engine='xlsxwriter')
df1.to_excel(writer, sheet_name='x1')
df2.to_excel(writer, sheet_name='x2')
# end ==>
# now create more new sheets
x3 = np.random.randn(100, 2)
df3 = pd.DataFrame(x3)
x4 = np.random.randn(100, 2)
df4 = pd.DataFrame(x4)
df3.to_excel(writer, sheet_name='x3')
df4.to_excel(writer, sheet_name='x4')
writer.save()
writer.close()
If you want to preserve all existing sheets, you can replace above code between begin and end with:
# read all existing sheets and write them back
writer = pd.ExcelWriter(path, engine='xlsxwriter')
xlsx = pd.ExcelFile(path)
for sheet in xlsx.sheet_names:
df = xlsx.parse(sheet_name=sheet, index_col=0)
df.to_excel(writer, sheet_name=sheet)
Another fairly simple way to go about this is to make a method like this:
def _write_frame_to_new_sheet(path_to_file=None, sheet_name='sheet', data_frame=None):
book = None
try:
book = load_workbook(path_to_file)
except Exception:
logging.debug('Creating new workbook at %s', path_to_file)
with pd.ExcelWriter(path_to_file, engine='openpyxl') as writer:
if book is not None:
writer.book = book
data_frame.to_excel(writer, sheet_name, index=False)
The idea here is to load the workbook at path_to_file if it exists and then append the data_frame as a new sheet with sheet_name. If the workbook does not exist, it is created. It seems that neither openpyxl or xlsxwriter append, so as in the example by #Stefano above, you really have to load and then rewrite to append.
#This program is to read from excel workbook to fetch only the URL domain names and write to the existing excel workbook in a different sheet..
#Developer - Nilesh K
import pandas as pd
from openpyxl import load_workbook #for writting to the existing workbook
df = pd.read_excel("urlsearch_test.xlsx")
#You can use the below for the relative path.
# r"C:\Users\xyz\Desktop\Python\
l = [] #To make a list in for loop
#begin
#loop starts here for fetching http from a string and iterate thru the entire sheet. You can have your own logic here.
for index, row in df.iterrows():
try:
str = (row['TEXT']) #string to read and iterate
y = (index)
str_pos = str.index('http') #fetched the index position for http
str_pos1 = str.index('/', str.index('/')+2) #fetched the second 3rd position of / starting from http
str_op = str[str_pos:str_pos1] #Substring the domain name
l.append(str_op) #append the list with domain names
#Error handling to skip the error rows and continue.
except ValueError:
print('Error!')
print(l)
l = list(dict.fromkeys(l)) #Keep distinct values, you can comment this line to get all the values
df1 = pd.DataFrame(l,columns=['URL']) #Create dataframe using the list
#end
#Write using openpyxl so it can be written to same workbook
book = load_workbook('urlsearch_test.xlsx')
writer = pd.ExcelWriter('urlsearch_test.xlsx',engine = 'openpyxl')
writer.book = book
df1.to_excel(writer,sheet_name = 'Sheet3')
writer.save()
writer.close()
#The below can be used to write to a different workbook without using openpyxl
#df1.to_excel(r"C:\Users\xyz\Desktop\Python\urlsearch1_test.xlsx",index='false',sheet_name='sheet1')
if you want to add empty sheet
xw = pd.ExcelWriter(file_path, engine='xlsxwriter')
pd.DataFrame().to_excel(xw, 'sheet11')
if you get empty sheet
sheet = xw.sheets['sheet11']
import pandas as pd
import openpyxl
writer = pd.ExcelWriter('test.xlsx', engine='openpyxl')
data_df.to_excel(writer, 'sheet_name')
writer.save()
writer.close()
The following solution worked for me:
# dataframe to save
df = pd.DataFrame({"A":[1,2], "B":[3,4]})
# path where you want to save
path = "./..../..../.../test.xlsx"
# if an excel sheet named `test` is already present append on sheet 2
if os.path.isfile(path):
with pd.ExcelWriter(path, mode='a') as writer:
df.to_excel(writer, sheet_name= "sheet_2")
else:
# if not present then write to a excel file on sheet 1
with pd.ExcelWriter(path) as writer:
df.to_excel(writer, sheet_name= "sheet_1")
Now, if you want to write multiple dataframes on different sheets, simply add a loop and keep on changing the sheet_name.
I am trying to build a simple python script that reads data from a .csv file, formats the data to an easy to read layout, then either writes it to a new xlsx file or appends to an existing xlsx file, depending on user input. That all works well and I write to the new file using;
with pd.ExcelWriter(file_path) as writer:
df.to_excel(writer, sheet_name='Master')
Now I want to add a second sheet that contains excel charts from the data and have extended the above code to;
with pd.ExcelWriter(file_path) as writer:
df.to_excel(writer, sheet_name='Master')
book = writer.book
sheet = writer.sheets['Master']
chart_a = book.add_chart({'type': 'line'})
chart_a.add_series({
'categories': ['Master', 1, 0, trend_data_row, 0],
'values': ['Master', 1, 1, trend_data_row, 1],
})
chart_a.set_x_axis({'name': 'time', 'position_axis': 'on_tick'})
chart_a.set_y_axis({'name': 'value'})
chart_a.set_legend({'position': 'Bottom'})
sheet.insert_chart('A11', chart_a)
writer.save()
This adds the chart to the 'Master' sheet as expected, I don't understand how to create the second sheet and insert the chart there instead. I have tried changing sheet = writer.sheets to a new name [Graphs] but I guess its looking for an existing sheet with that name rather than creating one. Any help is really appreciatted.
I don't understand how to create the second sheet and insert the chart there instead.
You can do it like this:
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_chart.xlsx', engine='xlsxwriter')
# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Master')
# Get the xlsxwriter workbook object.
workbook = writer.book
# Add a new worksheet.
worksheet = workbook.add_worksheet('Graphs')
# Create a chart object.
chart = workbook.add_chart({'type': 'column'})
# Configure the series of the chart from the dataframe data.
chart.add_series({'values': ['Master', 1, 1, 7, 1]})
# Insert the chart into the worksheet.
worksheet.insert_chart('D2', chart)
# Close the Pandas Excel writer and output the Excel file.
writer.save()
Output:
then either writes it to a new xlsx file or appends to an existing xlsx file
XlsxWriter cannot write to an existing file.
I'm creating an excel dashboard and I want to generate an excel workbook that has some dataframes on half of the sheets, and .png files for the other half. I'm having difficulty writing them to the same file in one go. Here's what I currently have. It seems that when I run my for loop, it won't let me add additional worksheets. Any advice on how I might get my image files added to this workbook? I can't find anything about why I can't add any more worksheets Thanks!
dfs = dict()
dfs['AvgVisitsData'] = avgvisits
dfs['F2FCountsData'] = f2fcounts
writer = pd.ExcelWriter("MyData.xlsx", engine='xlsxwriter')
for name, df in dfs.items():
df.to_excel(writer, sheet_name=name, index = False)
Then I want to add a couple sheets with some images to the same excel workbook. Something like this, but where I'm not creating a whole new workbook.
workbook = xlsxwriter.Workbook('MyData.xlsx')
worksheet = workbook.add_worksheet('image1')
worksheet.insert_image('A1', 'MemberCollateral.png')
Anyone have any tips to work around this?
Here is an example of how to get a handle to the underlying XlsxWriter workbook and worksheet objects and insert an 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', 'logo.png')
# Close the Pandas Excel writer and output the Excel file.
writer.save()
Output:
See also Working with Python Pandas and XlsxWriter in the XlsxWriter docs for more examples
Here's the solution I came up with. I still cound't find a way to do this without re-importing the workbook with load_workbook but this got the job done.
# assign dataframes to dictionary and export them to excel
avgvisits = pd.DataFrame(pd.read_sql(avgvisits(), cnxn))
f2fcounts = pd.DataFrame(pd.read_sql(f2fcounts(), cnxn))
activityencounters = pd.DataFrame(pd.read_sql(ActivityEncounters(), cnxn))
activityencountersp = activityencounters.pivot_table(values='ActivityCount', index = ['Activity'], columns= ['QuarterYear'], aggfunc=np.max)
dfs = dict()
dfs['AvgVisitsData'] = avgvisits
dfs['F2FIndirect'] = f2fcounts
dfs['ActivityEncounters'] = activityencountersp
writer = pd.ExcelWriter("MyData.xlsx", engine='xlsxwriter')
for name, df in dfs.items():
if name != 'ActivityEncounters':
df.to_excel(writer, sheet_name=name, index=False)
else:
df.to_excel(writer, sheet_name=name, index=True)
writer.save()
writer.close()
# re-import the excel book and add the graph image files
wb = load_workbook('MyData.xlsx')
png_loc = 'MemberCollateral.png'
wb.create_sheet('MemberCollateralGraph')
ws = wb['MemberCollateralGraph']
my_png = openpyxl.drawing.image.Image(png_loc)
ws.add_image(my_png, 'A1')
png_loc = 'DirectIndirect.png'
ws = wb['F2FIndirect']
my_png = openpyxl.drawing.image.Image(png_loc)
ws.add_image(my_png, 'A10')
png_loc = 'QuarterlyActivitySummary.png'
ws = wb['ActivityEncounters']
my_png = openpyxl.drawing.image.Image(png_loc)
ws.add_image(my_png, 'A10')
wb.save('MyData.xlsx')