Matplotlib Overlay Heatmap

How can I make the annotations and the x/y labels centered again. By default (), the name of the scale object or the name specified in labs() is used for the title. XXX APIs (or matplotlib. In R the pie chart is created using the pie() function which takes positive numbers as a vector input. Python source code: [download source: heatmap_annotation. Make sure to select the best rendering quality. colorbar(location) は、'northoutside' などの特定の位置にカラー バーを表示します。すべてのチャートのタイプで、カラー バーの位置の変更がサポートされているわけではありません。. The lowest level of these is plt. pyplot as plt import geopandas as gpd import pysal as ps from pysal. distplot(df['Difference']. Put module source code (heatmap. Visualizing the distribution of a dataset¶ When dealing with a set of data, often the first thing you'll want to do is get a sense for how the variables are distributed. Matplotlib and the Basemap libraries can probably do that. , python visualization correlation matplotlib heatmap. HeatMap requires a list of points, or a numpy array as input, so we need to first manipulate the data a bit:. I've tried packages like Fiona, basemap, GeoPandas, etc. Download an Adobe Swatch Exchange (ASE) file of this scheme. and you can overlay lines and use all the normal attributes to set the (of type heatmap and path,. Plot legends give meaning to a visualization, assigning meaning to the various plot elements. This opens the Plot Setup dialog box. 65, # the opacity of the heatmap layer colours = ' default ', # 'default' or 'reveal' # OR a matplotlib LinearSegmentedColorMap object # OR the path to a horizontal scale. )) Also, are there formats which support generating svg's which somehow support heatmaps intrinsically, i. A new post about maps (with improved examples!) can be found here. Using folium - 3: Heatmap (Heatmap of earthquakes) We talked in the previous blog how to query the USGS earthquake, and plot on the map. Ternary Plots. The count of the number of operations in the upper left-hand corner refers to the. Overlay a heatmap of the long/lat data; Is this correct? I'm looking for some guidance for a simple way where I can do this using Python 3. The limits of their axes (extent_L and extent_H) do not necessarily coincide exactly. New in version 0. Bases: matplotlib. My main blog where I post longer pieces is also on Dreamwidth. weights: array_like, optional. GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. In Matplotlib lexicon, i think you want a hexbin plot. Matplotlib's imshow function makes production of such plots particularly easy. 4 in order to make the colorbar smaller than the map and we are done. The cumulative overlap between the top three pairs of modes is 0. me keyword after analyzing the system lists the list of keywords related and the list of websites with related content, in addition you can see which keywords most interested customers on the this website. The matplotlib library comes with several built in styles. For example, you can control the minimum and maximum pixel values to show and the stretch function to use. Geographical plots. The Matplotlib defaults that usually don't speak to users are the colors, the tick marks on the upper and right axes, the style,… The examples above also makes another frustration of users more apparent: the fact that working with DataFrames doesn't go quite as smoothly with Matplotlib, which can be annoying if you're doing exploratory analysis with Pandas. pdf), Text File (. Let’s visualize a heatmap of the public transport stations in Helsinki using the addresses input data. I want to look at overlay between Pol II peaks and H3K4me1/H3K27Ac at intergenic regions. Admittedly, Basemap feels a bit clunky to use, and often even simple visualizations take much longer to render than you might hope. python,matplotlib,statsmodels,seaborn Seaborn is a great package for doing some high-level plotting with pretty outputs. This can be useful for a variety of things but when I first learned about it, I was a bit confused by how the axes seem to be flipped sometimes when you do this. basemap import Basemap import matplotlib. The 4th returning image seems to be the alpha channel and is mostly only white. using two-variable gradient area coloring?. How to change bubble chart color based on categories in Excel? If you want to change different bubble colors based on different categories in a bubble chart in Excel as below screenshot shown, this tutorial can help you. Plot rectangular data as a color-encoded matrix. Next, we'll plot the swarm plot. Announcing M_Map v1. The HTML/JavaScript generated in the dialog shown with Tools > Publish uses the Fusion Tables API to fetch the rows, parse them for use in the heatmap, and draw the map. I can imagine a heat map with superheros plotted on both axes could work for seeing interesting matches of one variable against all other ones, but it would still require some less ideal extra steps to see when three or more superheros matched, like seeing the colour overlap of superhero1 with superhero2 & superhero3 both be high, and that's. The function will calculate the kernel density estimate and represent it as a contour plot or density plot. I'm using Power BI Desktop offline (but do have access to internet on a seperate device). Change color of the boxes, whiskers, caps and the median The bp variable in the code snippet above is a python dictionary with keys boxes , whiskers , caps , fliers and the median. A lot of real world phenomena are continuous - elevations, soils, temperatures etc. While we can just plot a line, we are not limited to that. The below plot is my favorite data visualization I created for my thesis. jl heatmaps. Plotting with Geoplot and GeoPandas¶. This is an Axes-level function and will draw the heatmap into the currently-active Axes if none is provided to the ax argument. What is a heatmap? I A two-dimensional visualization of data using colour to represent magnitude I Broad de nition, which could be divided into I Embedded heatmaps that overlay colour on an actual map or image (not covered here) I Matrix heatmaps that presents a grid of values where colours di er by cell 2/30. What convolutional neural networks look at when they see nudity To build the heatmap on the left we send each window to our convnet and average the "NSFW" scores. 3 or lower, setting the display. To apply a style to your plot, just add: plt. jl, which is interesting because it talks to many of the other plotting packages. #24 Histogram with a boxplot on top | seaborn Histogram , seaborn Yan Holtz This chart is mainly based on seaborn but necessitates matplotlib as well, to split the graphic window in 2 parts. For help, join the gitter channel and the matplotlib-users , matplotlib-devel , and matplotlib-announce mailing lists, or check out the Matplotlib tag on stackoverflow. pyplot as plt import seaborn as sns sns. If the data is categorical, this would be called a categorical heatmap. h = heatmap(tbl,xvar,yvar,'ColorVariable',cvar) は cvar で指定された table 変数を使用して、カラー データを計算します。 既定の計算方法は、平均値の集計です。. Ternary Plots. Visualization of scalar and vector fields 2. Thanks in Advance!. ggplot2 graphics in a loop. js这款神器。然后搜了下例子,却很难搜到马上出效果的例子,特此写一篇heatmap. It shows the distribution of values in a data set across the range of two quantitative variables. It is very easy to use them, and allows to improve the quality of your work. Autocorrelation and partial autocorrelation plots are heavily used in time series analysis and forecasting. The output of the network is a heatmap depicting the likelihood of cancer at each pixel location. GDAL: Create Point Density Heatmap GeoTiff with Transparency 10-11-2016, 09:59 PM Basically, I would like to pass in a Density Map (#points per gridDelta) and generate a GeoTiff with built in colorRamping that I can then overlay on the map using a SurfaceImage. A geodesic line is the shortest path between two given positions on the earth surface. Overleaf comes with a complete, ready to go LaTeX environment which runs on our servers. Sub-clustering tubular cells in Morizane protocol (cluster PT1, PT2, and LH) and Takasato protocol (cluster PT1, PT2, LH, and Lp) were first combined, then sub-clustered using the same approach described above. HeatMap requires a list of points, or a numpy array as input, so we need to first manipulate the data a bit:. They are extracted from open source Python projects. This post shows how to achieve a very similar result using ggplot2. While we can just plot a line, we are not limited to that. Tony Finch's link log. This “4D” plot (x, y, z, color. plot (self, *args, **kwargs) [source] ¶ Call self as a function. The Hexagon layout requires both the X and Y axis columns to be numeric. This document explains PCA, clustering, LFDA and MDS related plotting using {ggplot2} and {ggfortify}. mpl_style to 'default' with pd. The following are code examples for showing how to use matplotlib. For example, you can compare sets of data, track changes in data over time, or show data distribution. If NULL, the title is not shown. We can see that cases not evenly distriubted throughout the country and most clusters are within a mile of another cluster. To apply a style to your plot, just add: plt. This is an Axes-level function and will draw the heatmap into the currently-active Axes if none is provided to the ax argument. GitHub Gist: instantly share code, notes, and snippets. Next, we'll plot the swarm plot. Image Overlay Using Transparency By Steve Eddins, MathWorks When we need to look at two images together—for example, to compare the input and output of a particular image processing operation, or to compare different images of the same scene—overlaying one image on top of the other is often more effective than viewing the images side-by-side. ly library inside the ipython notebook. A line chart can be created using the Matplotlib plot() function. Python-based portfolio / stock widget(app) which sources data from Yahoo Finance and calculates different types of Value-at-Risk (VaR) metrics and many other (ex-post) risk/return characteristics both on an individual stock and portfolio-basis, stand-alone and vs. To close the discussion about 3D, in this tutorial I’ll describe the impressive plot3D package and its extension plot3Drgl package. Search for jobs related to Extjs heatmap or hire on the world's largest freelancing marketplace with 15m+ jobs. OpenCV now comes with various colormaps to enhance the visualization in your computer vision application. js –最强大的Web动态热图最新公司项目需要用到热力图,在百度上搜下,了解到heatmap. pyplot as plt import geopandas as gpd import pysal as ps from pysal. Suppose you have a dataset containing credit card transactions, including: the date of the transaction; the credit card number; the type of the expense. The matplotlib, matplotlib-venn, and Seaborn plotting and visualization libraries were used for graphical data representation. Search for jobs related to Heatmap google or hire on the world's largest freelancing marketplace with 15m+ jobs. scatter¶ DataFrame. 1, pandas 0. In this post, I propose 10 charts allowing to avoid overplotting. Sign up Plotting data on google maps, the easy (stupid) way. import folium from folium import plugins import pandas as pd import matplotlib. Select a blank cell a few rows or columns away from the pivot table. Color Brewer sequential color schemes are built-in to the library, and can be passed to quickly visualize different combinations. 雷锋网成立于2011年,秉承“关注智能与未来”的宗旨,持续对全球前沿技术趋势与产品动态进行深入调研与解读,是国内具有代表性的实力型科技新. The heatmap in Figure 1 D shows the overlap (Marques and Sanejouand, 1995) between top-ranking PCA and ANM modes. Before we do that, allow me a digression into a bit of history of video capture. Line plots of observations over time are popular, but there is a suite of other plots that you can use to learn more about your problem. You can vote up the examples you like or vote down the ones you don't like. A visual representation of the selection sort algorithm sorting an array of 10, 50, and 100 integers from 1 to N. Welcome to the YouTube series on Seaborn, where we will be exploring this powerful and fascinating library while building some incredible visualizations! Learn the main operations and methods of. Build the chaco version of the animation plot, that is 3 contour plots displaying the concentration of one of the product components in the column liquid phase, in the bead liquid phase and in the bead-bound phase. Plot over an image background in MATLAB T his is a short tutorial that documents how to make a MATLAB plot on top of an image background. See also the index of other geographical charts. Useful when laying the heatmap over the original image, so that the image can be seen over the heatmap. One of the handiest visualization tools for making quick inferences about relationships between variables is the scatter plot. GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. animation_plot module¶. It’s so simple that it can run offline on a raspberry pi. Matplotlib was initially designed with only two-dimensional plotting in mind. To simulate the effect of stacked bar chart , the trick is to use multiple bar charts to overlay on top of each other to simulate the effect of stacked bar chart. Wind Rose and Polar Bar Charts. The Visualization Toolkit (VTK) is open source software for manipulating and displaying scientific data. However, for better and more quickly to analyze the benefit and stability of a department, I think the radar chart can be a good choice. exportimg() converts this into a working string. alpha_limit (float or int, optional) - Maximum alpha (transparency / opacity) value allowed for the alpha channel pixels in the RGBA heatmap image. More than a HOWTO, this document is a HOW-DO-I use Python to do my image processing tasks. It combines the protein 3D visualization capabilities of PyMOL and the protein's 2D contact map with an interactive interface for scientific analysis. boxplot( x = ' day ' , y = ' tip ' , data = tips, boxprops = dict ( alpha =. I have a set of X,Y data points (about 10k) that are easy to plot as a scatter plot but that I would like to represent as a heatmap. It can also fit scipy. GitHub Gist: instantly share code, notes, and snippets. KMLGenerator. Moreover, we will study syntax and examples of os Module in Python Programming Language. If your version of matplotlib is 1. RTL-SDR and GNU Radio with Realtek RTL2832U [Elonics E4000/Raphael Micro R820T] software defined radio receivers. Examples of how to make scientific charts such as contour plots, heatmaps, dendrograms, polar charts, and ternary plots. Conclusion. 207 Responses to How-To: Python Compare Two Images Xavier Paul November 26, 2014 at 4:53 am # Good day Adrian, I am trying to do a program that will search for an Image B within an Image A. Each bin also has a frequency between x and infinite. axis, so apply transpose to get a df with 5 columns representing countries and the years being the indices. Matplotlib provides an easy way of converting your yaxis to percentages. Note that you can use the same argument as for a 1D density plot to custom your chart. They are extracted from open source Python projects. pdf), Text File (. (*Needs flickR API key*) heatmapPNGgenerator. overlay import NdOverlay, Overlay fromcore. So I just overlayed each individually. import numpy as np import pandas as pd import matplotlib. Part of this Axes space will be taken and used to plot a colormap, unless cbar is False or a separate Axes is provided to cbar_ax. Note that you can use the same argument as for a 1D density plot to custom your chart. :type colormap: callable, optional:param alpha_limit: Maximum alpha (transparency / opacity) value allowed for the alpha channel pixels in the RGBA heatmap image. Seaborn Seaborn is a Python module exclusively for data visualization which was built on top of matplotlib. Here are some links to interesting web pages which I have encountered. This blog goes over the Matplotlib and Basemap components of the workshop. The central chart display their correlation. stripplot(). How to plot multiple data series in ggplot for quality graphs? I've already shown how to plot multiple data series in R with a traditional plot by using the par(new=T), par(new=F) trick. Python-based portfolio / stock widget(app) which sources data from Yahoo Finance and calculates different types of Value-at-Risk (VaR) metrics and many other (ex-post) risk/return characteristics both on an individual stock and portfolio-basis, stand-alone and vs. Bases: matplotlib. You can vote up the examples you like or vote down the ones you don't like. These are plots that graphically summarize the strength of a relationship with an observation in a time series with observations at prior time steps. Tony Finch's link log. Connected Scatter Correlogram Dendrogram Density Donut Heatmap Histogram Lineplot Lollipop Map Matplotlib Network. boxplot( x = ' day ' , y = ' tip ' , data = tips, boxprops = dict ( alpha =. My main blog where I post longer pieces is also on Dreamwidth. Python source code: [download source: heatmap_annotation. It’s just a one liner But the issue is you can’t space the yticks as you want them to be. There are many other things we can compare, and 3D Matplotlib is. You can generate intermediate GIS files and plots with GeoPandas, then shift over to QGIS. Posterize an image. If back is given (the default), the label is written underneath the graphed data. I've tried packages like Fiona, basemap, GeoPandas, etc. Each column represents an ordered pair. There are several options available for computing kernel density estimates in Python. , matplotlib, bokeh, seaborn, etc. To create it, the coordinates must be in a numpy array. Plotting with Geoplot and GeoPandas¶. I have two heatmaps which are based on 2d histograms that I am trying to overlay on a single graph. This piece closely follows Angelo Antonio Manzatto’s article on predicting sexual harassment by generating a heatmap of safe and unsafe spots. jl heatmaps. Manipulate your data in Python, then visualize it in a Leaflet map via folium. Color Brewer sequential color schemes are built-in to the library, and can be passed to quickly visualize different combinations. The Heatmap Layer is part of the google. colorbar(location) は、'northoutside' などの特定の位置にカラー バーを表示します。すべてのチャートのタイプで、カラー バーの位置の変更がサポートされているわけではありません。. csv() functions is stored in a data table format. It is a 2D density plot with histograms projected along each axis. Contribute to LumenResearch/heatmappy development by creating an account on GitHub. The size of 10x10 meter easily covers my whole apartment. 5 and ≤ − 1. resize() can be used. Commit Score: This score is calculated by counting number of weeks with non-zero commits in the last 1 year period. py] import matplotlib. It is a bit like looking a data table from above. It is built on top of the lower-level CartoPy, covered in a separate section of this tutorial, and is designed to work with GeoPandas input. and you can overlay lines and use all the normal attributes to set the (of type heatmap and path,. How to create radar chart/spider chart in Excel? There are various charts in Excel, and every type of chart has its own superiority. A visual representation of the selection sort algorithm sorting an array of 10, 50, and 100 integers from 1 to N. csv file; 6. One of my favorite new features in PROC SGPLOT in SAS 9. The image and DEM data is processed and generates a terrain heat map of the image as well as labels areas of the city which would be affected should the water level of the bay rise 10, 50, and 100 meters. js –最强大的Web动态热图最新公司项目需要用到热力图,在百度上搜下,了解到heatmap. 01) # Grid of 0. The Visualization Toolkit (VTK) is open source software for manipulating and displaying scientific data. 7,matplotlib,plot,histogram I want to draw a histogram and a line plot at the same graph. )) command line control over the. Here is the code from their website: mu = 100 #mean sigma = 15 #std deviation. js这款神器。然后搜了下例子,却很难搜到马上出效果的例子,特此写一篇heatmap. Create plots programmatically using graphics functions or interactively using the Plots tab at the top of the MATLAB ® desktop. Default is 0. Creating Scatterplots With Seaborn. Python's Seaborn module makes plotting a tidy dataset incredibly easy with '. Nice Python Basemap Background When using python Basemap to plot maps, a nice background would be a big plus. Subscribe to this blog. import os import argparse import csv import numpy as np from matplotlib import pyplot, image def draw_display(dispsize, imagefile=None): """Returns a matplotlib. Please try again later. The annotations in a Seaborn heatmap are centered in the middle of each cell by default. Here's what we'll do: First, we'll make our figure larger using Matplotlib. There are several valid complaints about matplotlib that often come up: Matplotlib’s defaults are not exactly the best choices. This section is a quick introduction to one of them, Plots. I have a heatmap image (correlation between all matrix columns) and I'm straggling to preform all the changes below within the same image: bar colors should be symmetric around zero (e. The Visualization classes are a self-contained library, separate from the main Maps JavaScript API code. The following are code examples for showing how to use matplotlib. , once-per-for loop), or you must manipulate your data to make it optimally fit the plot function (e. 1 Examples on plotting of scalar and vector fields We shall demonstrate visualization of scalar and vector fields using Matplotlib, Mayavi, and Matlab. Graphical Primitives Data Visualization with ggplot2 Cheat Sheet RStudio® is a trademark of RStudio, Inc. Default is matplotlib. Python, Matplotlib + Seaborn still stands out for its capability to create and customize all sorts of plots. Matplotlib's imshow function makes production of such plots particularly easy. These charts are based on pure HTML5/SVG technology (adopting VML for old IE versions) so no plugins are required. For other relationships we can try fitting a curve. com/showcase/) is. Matplotlib needs to be instructed which type of fonts to export with them, this is handled by using gs. Here's what we'll do: First, we'll make our figure larger using Matplotlib. You can vote up the examples you like or vote down the ones you don't like. The Visualization classes are a self-contained library, separate from the main Maps JavaScript API code. Ranges were provided for all medians. Color Brewer sequential color schemes are built-in to the library, and can be passed to quickly visualize different combinations. visualization library, and is not loaded by default. Annotations and line widths in Plots. One of my favorite new features in PROC SGPLOT in SAS 9. This post shows how to achieve a very similar result using ggplot2. The array must be of dtype float32. 雷锋网成立于2011年,秉承“关注智能与未来”的宗旨,持续对全球前沿技术趋势与产品动态进行深入调研与解读,是国内具有代表性的实力型科技新. Parameters: plot_func – A python function or callable to wrap. 0 release, some three-dimensional plotting utilities were built on top of Matplotlib's two-dimensional display, and the result is a convenient (if somewhat limited) set of tools for three-dimensional data visualization. XXX APIs (or matplotlib. Importing libraries and dataset. Density plot. If you're unsure what kernel density estimation is, read Michael's post and then come back here. Matplotlib honors the NumPy conventions for masked arrays, in that masked regions of two-dimensional plots are omitted. ly plots that are autosized don't look very good and I have tried to manually tweak them but they always get chopped up in the vertical direction of the notebook. The basic idea is that during interactive operations (e. k-Means is not actually a *clustering* algorithm; it is a *partitioning* algorithm. Source code for holoviews. 5 and ≤ − 1. % matplotlib inline import matplotlib. • CC BY RStudio • [email protected] colorbar_factory (cax, mappable, **kwargs) [source] ¶. pivot ("month", "year", "passengers") # Draw a heatmap with the numeric values in each cell f, ax = plt. Subscribe to this blog. Share a direct link to this color scheme. Reduction of true color values to a 256 color. It is a bit like looking a data table from above. I should stress that many of the plotting operations could be more quickly. I decided to put together this practical guide, which should hopefully be enough to get you up and running with your own. Matplotlib - bar,scatter and histogram plots from mpl_toolkits. In the example below, we added one more categorical variable [value = alpha, beta] in the plot with overlaying plots. This property could be used to scale the images, but here we are just using the actual pixel dimension of the PNG. gridspecを使用する方法もある。 この場合はgridspec. Its basically heatmap_rgb = plt. SGPLOT code for stacked bar chart with labels: Draw the bar segments using the HIGHLOW statement. Use plots to visualize data. For these data, it can be quite helpful to see a heatmap of the votes across the years. What you may want to do is to add a column to your dataset that will help Bing do a better job geocoding. mpl_style = 'default' to produce more appealing plots. The line chart, or line graph, connects several distinct data points, presenting them as one continuous evolution. Blend transparency with color in 2-D images¶. I would like make a bubble plot of canadain cities on a map. I have a set of X,Y data points (about 10k) that are easy to plot as a scatter plot but that I would like to represent as a heatmap. Load the visualization library. Graphical Primitives Data Visualization with ggplot2 Cheat Sheet RStudio® is a trademark of RStudio, Inc. View Tutorial. Cq 3C Yh Y2 r1 xS kO jU oR cH zY j4 W0 yn lV tT x0 29 cZ JF Wd 2z Hp uB Pr Dv J3 xI wi ce pX uh Oy md Ck ZH EV kR cC 25 Zc vC mB pM D1 mQ HM 5B 71 kV p8 sw Hr Z7 PD. I saw that. Using front will prevent a label from being obscured by dense data. Our system is in fact in no way limited to traffic data collection, and there may be hundreds of uses for it. nCounter-derived mRNA patterns of individual patients were normalized to the sum of the geometric mean of the internal positive controls and the housekeeping genes as recommended by the manufacturer. viz import mapping as maps In this lab, we will learn how to load, manipulate and visualize spatial data. Reduction of true color values to a 256 color. , python visualization correlation matplotlib heatmap. PDF | We introduce geoplotlib, an open-source python toolbox for visualizing geographical data. I based the above plot on code from here, however this plot also includes a 2D temperature/density plot in the middle, and 1/2/3 sigma contour lines. Conceptually, we can draw any matplotlib plot as a TensorFlow op. • CC BY RStudio • [email protected] 1 Examples on plotting of scalar and vector fields We shall demonstrate visualization of scalar and vector fields using Matplotlib, Mayavi, and Matlab. The Visualization classes are a self-contained library, separate from the main Maps JavaScript API code. This post presents a walk through of an object detection process applied to SpaceNet imagery. Here's what we'll do: First, we'll make our figure larger using Matplotlib. js heatmap representing time series data. Matplotlib's main tool for this type of visualization is the Basemap toolkit, which is one of several Matplotlib toolkits which lives under the mpl_toolkits namespace. jl is a plotting metapackage which brings many different plotting packages under a single API, making it easy to swap between plotting "backends". Karline Soetaert NIOZ-Yerseke The Netherlands Abstract Rpackage plot3D (Soetaert 2013b) contains functions for plotting multi-dimensional. There are hotspots that turn out to be postal sorting offices – PO boxes and post restante. exportimg() converts this into a working string. It's pretty straightforward to overlay plots using Seaborn, and it works the same way as with Matplotlib. folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. A line chart can be created using the Matplotlib plot() function. Plots wind barbs on the map. Using folium - 3: Heatmap (Heatmap of earthquakes) We talked in the previous blog how to query the USGS earthquake, and plot on the map. The alternative is Android. The shapes, in this case, are of the type Polygon. Creating a Graph provides an overview of creating and saving graphs in R. 4m2 is addition of the COLORRESPONSE= and COLORMODEL= options to the SCATTER statement. 5 and ≤ − 1. mplot3d import Axes3D import matplotlib. The count of the number of operations in the upper left-hand corner refers to the. Related course: Matplotlib Intro with Python. This page displays many examples built with R, both static and interactive. How to plot data onto maps in Python? Close. jl is a plotting metapackage which brings many different plotting packages under a single API, making it easy to swap between plotting "backends". Let's get started! If you've started doing some data visualisation with Matplotlib and Pandas, but are looking for the next simple step to getting started with geographical data, I got you. This section is a quick introduction to one of them, Plots. 热图绘制函数heatmap. Pillow for enterprise is available via the Tidelift Subscription. pyplot as plt import seaborn. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: