Manage date-time visualization of a dataframe with matplotlib and jupyter-CodePudding

I'm new to pandas and matplotlib and I have a dataframe in the form of

                            Info    Temp
2022-06-06  16:34:51,389    DEBUG   55 
2022-06-06  16:34:51,482    DEBUG   56
2022-06-06  16:34:51,581    DEBUG   57

Using pd.read_csv('debug.log', sep=' ') it correctly shows the dataframe and automatically recognize the time and the day

Now, I'm able to plot the data with no issue using table['Temp'].plot() The problem is the graph is super small and the data in the x-axis are overlapped.

Is there a way to make the x-axis labels rotated and zoom in the graph? I've tried plt.gcf().autofmt_xdate() but it does nothing.

CodePudding user response：

Ok so just using table['temp'].plot(rot=45,figsize=(100,10)) and right-clicking I can see the graph with a decent size

Documentation if needed