std ( axis =- 1, keepdims = True ) # calculate the covariance matrix covariance = np. mean ( axis =- 1, keepdims = True ) normalized_price_changes /= price_changes. diff ( prices ) # Below is a pretty standard way of normalizing numerical data normalized_price_changes = price_changes - price_changes. load ( "data/stock-prices.npz" ) names = meta good_idx = meta # only plot the ones for which we were able to parse sector info data_colors = meta # calculate the daily price difference price_changes = np. Import pickle with open ( "data/stock-metadata.pickle", "rb" ) as f : meta = pickle.
Scatter plot matplotlib even odd points code#
The data was originally obtained from and the data was cleaned using code derived from PCA of Stock Data #įor this example we will plot companies in SP500 in a scatter plot by principle components extracted from principal components analysis (PCA) an interactive visualization of companies in SP500 using PCA. However, you can use custom functions for the interactive plots, or even attach your own callbacks to the scatter_selector widgets. In this example we will use scatter_selector_index along with the indexer convenience function to make line plots of stock data. Scatter_selector_index: callbacks will receive index Scatter_selector_value: callbacks will receive x, y Scatter_selector: callbacks will receive index, (x, y) where index is the position of the point in the of the points. There are three variants that differ only in what they pass to their callbacks: , passing a function willĪutomatically create a set of custom matplotlib widgets that allow you to select points on a scatter plot as use that as input to other interactive plots. show ()įinally, we can specify functions for the formatter using FormatStrFormatter ( ' %1.5f ' ) locator = matplotlib.
set_major_locator ( locator ) formatter = matplotlib. set_major_formatter ( formatter ) formatter = matplotlib. MaxNLocator ( nbins = 'auto', steps = ) axs. FormatStrFormatter ( ' %1.1f ' ) locator = matplotlib. subplots ( 2, 2, figsize = ( 8, 5 ), tight_layout = True ) for n, ax in enumerate ( axs. Ticklabels are quite large, so we set nbins=4 to make theįig, axs = plt. Is not (because its not yet known.) In the bottom row, the Ticklabel is taken into account, but the length of the tick string Nbins=auto uses an algorithm to determine how many ticks willīe acceptable based on how long the axis is. However, 3, 6, 9 would not beĪcceptable because 3 doesn't appear in the list of steps. The steps keyword contains a list of multiples that can be used for Ticker.MaxNLocator(self, nbins='auto', steps=) text ( 3, 8, 'boxed italics text in data coords', style = 'italic', bbox = °' ) plt. set_ylabel ( 'ylabel' ) # Set both x- and y-axis limits to instead of default ax. suptitle ( 'bold figure suptitle', fontsize = 14, fontweight = 'bold' ) ax. subplots_adjust ( top = 0.85 ) # Set titles for the figure and the subplot respectively fig. Import matplotlib import matplotlib.pyplot as plt fig = plt.
Shows all of these commands in action, and more detail is provided in the The following commands are used to create text in the pyplotĪll of these functions create and return a Text instance, which can beĬonfigured with a variety of font and other properties. Math symbols and commands, supporting mathematical expressions anywhere in your figure. Or scientific figures, Matplotlib implements a large number of TeX Weight, text location and color, etc.) with sensible defaults set inĪnd significantly, for those interested in mathematical The user has a great deal of control over text properties (font size, font Matplotlib.font_manager (thanks to Paul Barrett), which Produces very nice, antialiased fonts, that look good even at small Or PDF, what you see on the screen is what you get in the hardcopy. Vector outputs, newline separated text with arbitraryīecause it embeds fonts directly in output documents, e.g., for postscript Mathematical expressions, truetype support for raster and Matplotlib has extensive text support, including support for Introduction to plotting and working with text in Matplotlib.
Scatter plot matplotlib even odd points full#
To download the full example code Text in Matplotlib Plots #
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