Another simple way is to use the pandas.DataFrame.pivot function to format the data. Use pandas.DataFrame.plot to plot. Providing the colors in the ‘color’ column exist in matplotlib: List of named colors, they can be passed to the color parameter.
If you don’t care which version of Plotly you install, just use pip. pip install plotly is an easy way to install the latest stable package for Plotly from PyPi. pip is a useful package and dependency management tool, which makes these things easy, but it should be noted that Anaconda’s conda tool will do the same thing. pip will install … Read more
You’re passing in specific rgb values, so matplotlib can’t construct a colormap, because it doesn’t know how it relates to your original data. Instead of mapping the values to RGB colors, let scatter handle that for you. Instead of: Do: (Just pass in to c what you were originally passing into plt.cm.jet.) Then you’ll be … Read more
The issue is because plot() is looking for vectors, and you’re feeding it one data.frame and one vector. Below is an illustration of some of your options.
You can use axis: That is, something like this:
You want something like the cex=1.5 argument to scale fonts 150 percent. But do see help(par) as there are also cex.lab, cex.axis, …
The plt.tick_params method is very useful for stuff like this. This code turns off major and minor ticks and removes the labels from the x-axis. Note that there is also ax.tick_params for matplotlib.axes.Axes objects.
They all do different things, since matplotlib uses a hierarchical order in which a figure window contains a figure which may consist of many axes. Additionally, there are functions from the pyplot interface and there are methods on the Figure class. I will discuss both cases below. pyplot interface pyplot is a module that collects a couple of … Read more
You could explicitly set where you want to tick marks with plt.xticks: For example, (np.arange was used rather than Python’s range function just in case min(x) and max(x) are floats instead of ints.) The plt.plot (or ax.plot) function will automatically set default x and y limits. If you wish to keep those limits, and just change the stepsize of the tick marks, then you could use ax.get_xlim() to discover what limits Matplotlib … Read more
To change the labels for Pandas df.plot() use ax.legend([…]): Another approach is to do the same by plt.legend([…]):