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Differences in well-log plotting between Jupyter Notebook and Power BI

I'm using python visuals for plotting 2 columns (DEPTH and GR) of a Well-Log dataset in a "vertical line chart".


The target chart looks like this:



The Python script in jupyter notebook is pretty simple:


import lasio
file_path = "Well-Logs-and-Petrophysics/Data/15-9-19_SR_COMP.LAS"
las =
df = las.df()
df.reset_index(drop=False, inplace=True)
df.rename(columns={'index': 'Index', 'DEPT':'DEPTH'}, inplace=True)
df.dropna(how='any', axis=0, inplace=True)

x = df['GR']
y = df['DEPTH']
plt.plot(x, y)



For loading the data into Power BI, I'm using the same firsts lines to read (and clean) the LAS file as a dataframe.


Finally, I'm using the using the following code for the python visual:


import matplotlib.pyplot as plt 

dataset.plot(kind='line', x='GR', y='DEPTH')



But the image plotted is the following:



The python script is the same as in jupyter notebook, than in power bi, but power BI is not plotting the same way.



What is happening, and how to achieve desired well-log visualization in Power BI using Python visuals


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