I have an excel file including some charts. The file is big and complicated and The data is coming from an external source, it means that the data is not included in the excel file discretely, and the only way to see the data is to extract it from the charts. I know how to do this in Excel, but I am looking for a way to read the data from the charts in python(Instead of reading the tabular data).
Is there way to save a "Figure" in matplotlib to a file such that if you later wanted to modify the Figure, e.g. change data points, resize the figure, etc. you could load up the file in a new python script and do that?
Right now I save the majority of my plots as Pdfs, but that doesn't allow me to make edits later on. I have to go dig up my old source code and data files. I've lost track of the number of times I've lost the plot-generating code and have to essentially reproduce it all from scratch.
It would be nice if I could just save a plot as a self-contained data file, like Photoshop does with its .psd files, so that I can just load it up directly, type "object.plot()", and not have to worry about external dependencies. Does such a format exist, or if not is there any way I could achieve this?
There is a method of saving the plotted object called pickling. I don't have much experience with it but it should allow you to save the plot to a file using
fig = plt.figure
pl.dump(fig, file('file_name.pickle','w'))
and using
fig = pl.load(open('file_name.pickle','rb'))
fig.show()
to load the saved graph.
Matplotlib warns that, "Pickle files are not designed for long term storage, are unsupported when restoring a pickle saved in another matplotlib version". To be safe, I would just save the array containing the data to the plot to either a .csv or .txt file, and keep this file in a folder with the python file to plot the graph. This way you will always be able to plot your data (no matter the version of matplotlib you are using). You will also have the data and code in the same place, and you can easily read the data from the .csv or .txt file, save it to arrays, and graph it using
file = open("file_name.txt", "r")
if file.mode == 'r':
data = f.read().splitlines()
data_array1 = data[0].split(",")
data_array2 = data[1].split(",")
p, = plt.plot(data_array1, data_array2)
I also suggest uploading your python files along with your .csv or .txt files to Github.
If you would like to read more about pickling in matplotlib I suggest reading the two pages linked below.
(1) Pickle figures from matplotlib
and (2) https://matplotlib.org/3.1.3/users/prev_whats_new/whats_new_1.2.html#figures-are-picklable
I created a script in python and use pcolormesh to plot an intensity graph. I want to save the data in that plot with specific resolution in .mat file to be used by another software.
How to extract data from plot data filter in paraview through python script?? I want to get data through python script by which paraview is drawing the graph.
If anyone know this answer please help
Thank you
Usually plots are made by plotting one data array versus another. You can often obtain that data directly from the filter/source that produced it and save it to a CSV file. To do this, select
You can save data from a filter as a CSV file by selecting the filter/source in the Pipeline Browser and choosing File -> Save Data. Choose the CSV File (*.csv) file type. Arrays in the filter/source output are written to different columns in the CSV file.
I am working in python and using xlwt.
I have got a sample excel sheet and have to generate same excel sheet from python. Now the problem is heading columns are highlighted using some color from excel color palette and I am not able to find the name of color. I need to generate exact copy of sample given to me.
Is there any function in xlwt which let me read color of cell of one sheet and then put that color in my sheet?
Best you read the colours from the sample given to you with xlrd.
If there are only a few different colours and they stay the same over time, you can also open the file in Excel and use a colour picker tool to get the RGB values of the relevant cells.