How To Upload A Schedule In Arena Simulation With A Excel File

How to Work with Excel files in Pandas

A few useful things to know when you have the data in Excel format

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From what I have seen then far, CSV seems to be the most pop format to store information amidst information scientists. And that's understandable, it gets the job done and information technology's a quite unproblematic format; in Python, even without any library, ane can build a simple CSV parser in under 10 lines of code.

Just you lot may not always find the data that you need in CSV format. Sometimes the only bachelor format may be an Excel file. Like, for example, this dataset on ons.gov.uk near crime in England and Wales, which is only in xlsx format; dataset that I will employ in the examples below.

Reading Excel files

The simplest fashion to read Excel files into pandas information frames is by using the post-obit function (bold yous did import pandas every bit pd):

df = pd.read_excel('path_to_excel_file', sheet_name='…')

Where sheet_name can exist the name of the sheet we desire to read, information technology's alphabetize, or a listing with all the sheets we want to read; the elements of the listing tin can be mixed: canvass names or indices. If we want all the sheets, nosotros can utilize sheet_name=None. In the case in which we want more sheets to be read, they will be returned as a lexicon of data frames. The keys of such a dictionary volition be either the index or name of a sail, depending on how we specified in sheet_name; in the example of sheet_name=None, the keys will be canvas names.

Now, if nosotros use information technology to read our Excel file we get:

That's right, an error! Information technology turns out that pandas cannot read Excel files on its own, so nosotros need to install another python bundle to do that.

In that location are 2 options that nosotros have: xlrd and openpyxl. The package xlrd can open both Excel 2003 (.xls) and Excel 2007+ (.xlsx) files, whereas openpyxl can open only Excel 2007+ (.xlsx) files. And so, we will install xlrd as information technology can open up both formats:

pip install xlrd

At present, if we effort to read the aforementioned data once more:

Information technology works!

But Excel files tin can be a little chip messier. Besides information, they may take other comments/explanations in the first and/or final couple of rows.

To tell pandas to start reading an Excel sheet from a specific row, use the argument header = 0-indexed row where to commencement reading. By default, header=0, and the offset such row is used to give the names of the data frame columns.

To skip rows at the end of a sheet, utilise skipfooter = number of rows to skip.

For case:

This is a piffling better. There are still some problems that are specific to this data. Depending on what we want to achieve we may also need to rearrange the information values into another way. Merely in this article, we will focus simply on reading and writing to and from data frames.

Another way to read Excel files too the i above is past using a pd.ExcelFile object. Such an object can exist constructed by using the pd.ExcelFile('excel_file_path') constructor. An ExcelFile object tin be used in a couple of ways. Firstly, it has a .sheet_names aspect which is a list of all the canvass names within the opened Excel file.

Then, this ExcelFile object also has a .parse() method that can be used to parse a sheet from the file and return a information frame. The first parameter of this method can be the alphabetize of the sheet we want to parse or its name. The balance of the parameters are the aforementioned as in the pd.read_excel() function.

An case of parsing the 2d sheet (index 1):

… and hither nosotros parse the same sheet using its name instead of an index:

ExcelFilesouth tin likewise be used inside with … as … statements, and if you desire to do something a little more elaborate, like parsing only sheets with 2 words in their name, yous tin do something like:

The same thing you tin do by using pd.read_excel() instead of .parse() method, like this:

… or, if y'all simply desire all the sheets, yous can do:

Writing Excel Files

Now that we know how to read excel files, the next step for us is to be able to also write a information frame to an excel file. We can exercise that past using the information frame method .to_excel('path_to_excel_file', sheet_name='…').

Let's beginning create a simple data frame for writing to an excel file:

Now we want to write it to an excel file:

… and nosotros got an error.

Over again, pandas can't write to excel files on its ain; nosotros need another package for that. The chief options that we take are:

xlwt — works merely with Excel 2003 (.xls) files; append style non supported
xlsxwriter — works only with Excel 2007+ (.xlsx) files; append fashion not supported
openpyxl — works only with Excel 2007+ (.xlsx) files; supports append mode

If we want to exist able to write to the onetime .xls format we should install xlwt as it is the but that handles those files. For .xlsx files, we will choose openpyxl as it as well supports the append way.

pip install xlwt openpyxl

Now if we run over again the above code, it works; an excel file was created:

By default, pandas also writes the index column along with our columns. To get rid of it, use index=False like in the code below:

The index cavalcade isn't there now:

What if nosotros want to write more sheets? If we desire to add a second canvass to the previous file, do yous recollect that the below code will work?

The answer is no. It volition just overwrite the file with only one sheet: sheet2.

To write more sheets to an Excel file we need to utilise a pd.ExcelWriter object every bit shown beneath. Offset, we create another data frame for sheet2, and then nosotros open up an Excel file as an ExcelWriter object in which we write the 2 data frames:

Now our Excel file should have 2 sheets. If we and so desire to add some other sheet to information technology, nosotros demand to open the file in append mode and run code similar to the previous ane. For case:

Our Excel file, now, has 3 sheets and looks like this:

Working with Excel Formulas

Probably you are wondering, at this point, about Excel formulas. What about them? How to read from files that have formulas? How to write them to Excel files?

Well… skilful news. It is quite like shooting fish in a barrel. Writing formulas to Excel files is as elementary equally just writing the cord of the formula, and these strings will be automatically interpreted by Excel equally formulas.

Equally an instance:

The Excel file produced by the lawmaking higher up is:

Now, if we want to read an Excel file with formulas in it, pandas will read into data frames the result of those formulas.

For example, let's read our previously created file:

Sometimes you need to save the Excel file manually for this to piece of work and not become zeros instead of the event of formulas (hit CTRL+S before executing the above code).

Below is the code equally a Jupyter notebook:

I promise you lot found this information useful and cheers for reading!

This commodity is also posted on my ain website here. Feel free to have a look!