Mar-23-2024, 10:55 PM
I have a dataset that I'm importing from a CSV into a dataframe in python. I need to make a simple line graph out of it.
Here is my code:
plt.gca().xaxis.set_major_formatter(ticker.ScalarFormatter(useMathText=False))
plt.ticklabel_format(useOffset=False)
plt.gca().xaxis.set_major_formatter(ticker.ScalarFormatter(useOffset=False))
And still it's showing as scientific notation. Any advice on how to force it to use the full number?
Here is my code:
# Create the line graph plt.plot(x_values, y_values, marker='o', linestyle='-') # Customize the x-axis tick formatter #plt.gca().xaxis.set_major_formatter(ticker.ScalarFormatter(useMathText=False)) plt.ticklabel_format(useOffset=False) #plt.gca().xaxis.set_major_formatter(ticker.ScalarFormatter(useOffset=False)) # Add labels and title plt.xlabel('X') plt.ylabel('Y') plt.title('Data') # Display the graph plt.grid(True) # Add grid lines plt.show()So my Y axis data ranges in value from 190-197 and has a precision of two decimal places. Simple enough. My X axis data however is time measured in nanoseconds - and my data set spans an hour of time starting at 34200001686628 and ending at 37798014509685 - I have about 27300 data points in my data set. I am graphic this because I want to be able to zoom in and look at the microscale data when graphed. The problem is no matter what I seem to try, matplotlib uses scientific notation on the X axis. In order to make sense of my data, I need to see the full timestamps - with no scientific notation. I have tried:
plt.gca().xaxis.set_major_formatter(ticker.ScalarFormatter(useMathText=False))
plt.ticklabel_format(useOffset=False)
plt.gca().xaxis.set_major_formatter(ticker.ScalarFormatter(useOffset=False))
And still it's showing as scientific notation. Any advice on how to force it to use the full number?