# Numpy Percentile Ignore 0

Numpy and Matplotlib¶These are two of the most fundamental parts of the scientific python "ecosystem". Title: Birth to 36 months: Boys, Length-for-age and Weight-for-age percentiles Author: NCHS Subject: CDC Growth Charts: United States Keywords: Growth Charts, NHANES, Birth to 36 months: Boys, Length-for-age and Weight-for-age percentiles. That makes picking out the highlights somewhat arbitrary but the following may be of particular interest or indicate areas likely to have future consequences. Editado el 13 de junio de 2012: Añadidas funciones para crear arrays de NumPy a partir de listas y una nota sobre el peligro de la función empty. I have fixed the example and made it clearer how the percentile values are calculated (so they can be debugged by the skeptical developers we should be). The default is to compute the percentile(s) along a flattened version of the array. weights – Weights computed for every feature. The 0th percentile is essentially equivalent to the Minimum statistic, and the 100th percentile is equivalent to Maximum. Combined statistical representations with distplot figure factory¶. statisticslectures. You can vote up the examples you like or vote down the ones you don't like. val asc) over (partition by sttr. percentile(arr, n, axis=None, out=None) Parameters : arr :input array. It is important to note several features of these OLS functions. Highlights¶. View Thomas H Lipscomb’s profile on LinkedIn, the world's largest professional community. This module trains the author-topic model on documents and corresponding author-document dictionaries. In python: import numpy as np n_samples = 30 desired_percentile = 90 x = np. As I've described in a StackOverflow question, I'm trying to fit a NumPy array into a certain range. Missing Data can also refer to as NA(Not Available) values in pandas. Quantile Regression Forests Introduction. sql - A script to create the two functions below and run them to produce some sample results. “Quantile Regression. Numpy提供各种统计函数，用于数据统计分析。 从数组中找出最小和最大元素 函数numpy. First part may be found here. -in CuPy column denotes that CuPy implementation is not provided yet. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. nanpercentile (a, q[, axis, out, ]) Compute the qth percentile of the data along the specified axis, while ignoring nan values. Pandas is an opensource library that allows to you perform data manipulation in Python. Some software programs (including Microsoft Excel ) regard the minimum and maximum as the 0th and 100th percentile, respectively; however, such terminology is an extension beyond traditional. For example, to find the 25% of values that appear above the mean, set percentile_distance to 25, func to "mean" and direction to one. Rozier has never ranked above the 37th percentile at his position in points per shot attempt, and his assist percentage topped out in the 44th. If you're interested, download the Excel file. 概要 numpy の統計量を計算する関数を整理する。 概要 numpy. NumPy is a commonly used Python data analysis package. INC, PERCENTILE. classification module¶ class pyspark. 75*39) = ceil(29. But it always returns a scalar. The NumPy 1. To control this, I added the perc parameter, which sets the percentile of the shadow features' importances, the algorithm uses as the threshold. Python numpy 模块， nan_to_num() 实例源码. ''' Build a tweet sentiment analyzer ''' from __future__ import print_function import six. A float number has a decimal in it. n : percentile value. ndarray`, optional If specified, the output values will be placed in this array (typically used for in-place calculations). pyplot as plt import seaborn as sns from mpl_toolkits. Create your free Platform account to download our ready-to-use ActivePython or customize Python with any packages you require. Remember, python is a zero indexing language unlike R where indexing starts at one. In order to operate the images in 3D, we need to import and stack the images successively. matrix) data. There are two main percentile functions in Power BI: PERCENTILE. how to install numpy on python on windows 10 Allround Zone. percentile(a, q=[10,25,50,75,90], axis=0). Note: The second argument of the PERCENTILE function must be a decimal number between 0 and 1. It can be a string of the format “percentile(float)” to denote that percentile of the feature’s value used on the x-axis. # -*- coding: utf-8 -*-# transformations. percentile(weight_array(ar, weights), 25). My problem now is, that the result is not 100% correct and I suspect it. This can be accomplished using different methods in SAS with some variation in the output. @parameter key - optional key function to compute value from each element of N. By using NumPy, you can speed up your workflow, and interface with other packages in the Python ecosystem, like scikit-learn, that use NumPy under the hood. The following are code examples for showing how to use numpy. -the lowest score is "in the 1st percentile" (there is no 0 percentile rank) -the highest score is "in the 99th percentile" (you can't score in the 100th percentile because you can't beat your own score) If you "scored in the 66th percentile", you scored "as well as or better than" 66% of the group. " A percentile, like a quartile or a decile, is a point, not a range. 18 Most Common Python List Questions Discover how to create a list in Python, select list elements, the difference between append() and extend(), why to use NumPy and much more. In contrast, numpy. A new format 2. Hi, with an ARRAY formula =PERCENTILE(IF(K4:AP40,K4:AP4),0. isscalar in that numpy. 5 * the IQR experimental analysis has shown that a higher/lower IQR might produce more accurate results. nanmean numpy. This article is a brief introduction to pandas with a focus on one of its most useful features when it comes to quickly understanding a dataset: grouping. percentile(x,70,interpolation="nearest") 2. Many of us, computer engineers, might be messed up with Python packages or modules, installing and uninstalling packages with different tools and making it work by chance after many trials. vstack、hstack は、配列を縦（vstack）、または横（hstack）に連結します。Numpy の concatenate でも同様の処理が可能です。. Statistics : Computing Mean,Variance, Percentiles, Correlations in Python In [1]: import pandas as pd import numpy as np import matplotlib. Importing the NumPy module There are several ways to import NumPy. In this part, I go into the details of the advanced features of numpy that are essential for data analysis and manipulations. is this good? i dont quite know what that means. 3 indicates 30 percent. Select a blank cell that you want to place the result, enter this formula =PERCENTILE(IF(A1:A18,A1:A18),0. matplotlibでどれだけめんどうかを把握した上で使う方がいい. Percentile or sequence of percentiles to compute, which must be between 0 and 100 inclusive. mean(a) a is a list of numbers. SegmentFault 思否是中国领先的新一代开发者社区和专业的技术媒体。我们为中文开发者提供纯粹、高质的技术交流平台以及最前沿的技术行业动态，帮助更多的开发者获得认知和能力的提升。. transpose()) must work on arrays of arbitrary dimension. Oct 12, 2017. -the lowest score is "in the 1st percentile" (there is no 0 percentile rank) -the highest score is "in the 99th percentile" (you can't score in the 100th percentile because you can't beat your own score) If you "scored in the 66th percentile", you scored "as well as or better than" 66% of the group. ceil taken from open source projects. Updated PRs (new commits but old needs-work label) [9] gh-14669: BUG: Do not rely on undefined behaviour to cast from float to datetime. This can be exceeded by structured arrays with a large number of columns. prepare_data. Different ways of calculating percentiles using SAS Arun Akkinapalli, eBay Inc, San Jose CA ABSTRACT Calculating percentiles (quartiles) is a very common practice used for data analysis. This book covers the basics of SciPy and NumPy with some additional material. 1) This is an array formula which must be entered by pressing CTRL+Shift+Enter 'and not just Enter. -the lowest score is "in the 1st percentile" (there is no 0 percentile rank) -the highest score is "in the 99th percentile" (you can't score in the 100th percentile because you can't beat your own score) If you "scored in the 66th percentile", you scored "as well as or better than" 66% of the group. How to find the memory size of any array (★☆☆) 5. OpenCV-Python makes use of Numpy, which is a highly optimized library for numerical operations with a MATLAB-style syntax. Create a random vector of size 30 and find the mean value. out : `~numpy. Repeat this for all neighborhoods, i. Many of us, computer engineers, might be messed up with Python packages or modules, installing and uninstalling packages with different tools and making it work by chance after many trials. percentiles. correlate numpy. In NumPy versions <= 1. First part may be found here. percentile(x,70) # 70th percentile 2. See contextlib. Lets start by defining a simple Series and DataFrame on which to demonstrate this: import pandas as pd import numpy as np rng = np. So the values are all the same except for the zero in C13. L'elenco delle istruzioni e delle funzioni scientifiche del modulo numpy. unif Stack Exchange Network Stack Exchange network consists of 175 Q&A communities including Stack Overflow , the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. No obstante!, también es posible hacer operaciones con matrices de diferentes tamaños si Numpy puede transformar estos arreglos en arreglos del mismo tamaño: esta conversión se llama broadcasting. Therefore, it can't really be converted into an IQ. Efficient rolling statistics with NumPy. nonzero(a)[source] Return the indices of the elements that are non-zero. ndarray of the shape(96, 4800, 4800) - in other words 96 satellite images each measuring 4800 by 4800 pixels. 9 the returned array is a read-only view instead of a copy as in previous NumPy versions. corrcoef numpy. There are several real-life reasons why paylines (the ones that use percentiles) can be either higher or lower than success rates. Hi all, running into an error and i'm not sure why when I am trying to rank the attribute field of a shapefile. NumPy is a commonly used Python data analysis package. Beta distribution (percentile) Calculator - High accuracy calculation Welcome, Guest. Instead, it is common to import under the briefer name np:. percentile(a, q=[10,25,50,75,90], axis=0). Practical Data Mining with Python Discovering and Visualizing Patterns with Python Covers the tools used in practical Data Mining for finding and describing structural patterns in data using Python. array(1)), while this is True for quantities, since quantities cannot represent true numpy scalars. axis : axis along which we want to calculate the percentile value. Alongside, it also supports the creation of multi-dimensional arrays. percentile() 百分位数是统计中使用的度量，表示小于这个值的观察值的百分比， 如果提供了轴，则沿其计算。 numpy. 23300000000000001 NUMBER also supports lists of floating-point numbers – in fact, it matches floating-point numbers appearing anywhere in the output, even inside a string! This means that it may not be appropriate to enable globally in doctest_optionflags in your configuration file. @parameter key - optional key function to compute value from each element of N. The difference is that PERCENTILE and PERCENTILE. 18 PERCENTILE. The default is 90, for the 90th percentile. I cannot find a formula to median. Here is an extremely simple logistic problem. concatenate() 2個以上の配列を軸指定して結合する。 軸指定オプションのaxisはデフォルトが0 マスクは保存されない。. This tutorials uses a small dataset provided by the Cleveland Clinic Foundation for Heart Disease. PERCENTILE. Returns the standard deviation, a measure of the spread of a distribution, of the non-NaN array elements. Raster objects. The standard approach is to use a simple import statement: >>> import numpy However, for large amounts of calls to NumPy functions, it can become tedious to write numpy. the number of documents. More than 1 year has passed since last update. Missing Data is a very big problem in real life scenario. samplewise_zero_center. At the end of data analysis, you could have a model and a set of. On the other hand, if the percentile is calculated as close to 50 then we know that it's close our our central tendency. basemap import Basemap % matplotlib inline import warnings warnings. Typically, we use the 25th and 75th percentiles of the data as the start and endpoints of the box and draw a line within the box for the 50th percentile (the median). concatenate() 2個以上の配列を軸指定して結合する。 軸指定オプションのaxisはデフォルトが0 マスクは保存されない。. In python: import numpy as np n_samples = 30 desired_percentile = 90 x = np. isscalar returns False for a zero-dimensional array (e. Corresponds to Kappa from Matthew D. numpy で np. Matlab/Octave (optional): The library is compatible with any Matlab from 2010 and Octave. 0729677997904314 The latter is an actual entry in the vector, while the former is a linear interpolation of two vector entries that border the percentile. The NumPy 1. Elastic Cloud Pricing. The window is centred on a certain calendar day, for example: - April 13th, we take the values for April 11th, April 12th, April 13th, April 14th and April 15th of each year of the base period. percentile(correct_array, 50). Here are the examples of the python api numpy. Explains predictions on Image (i. percentile を使って以下のように記述できます。. Possible types are: ‘num’, ‘percent’, ‘max’, ‘min’, ‘formula’, ‘percentile’. How to median values ignore zeros or errors in Excel? To median a range ignoring zero values, you can apply below formula. The main scenario considered is NumPy end-use rather than NumPy/SciPy development. 0 release contains a large number of fixes and improvements, but few that stand out above all others. This tutorial provides an example of how to load pandas dataframes into a tf. Interestingly, after 1000 runs, removing outliers creates a larger standard deviation between test run results. matplotlibでどれだけめんどうかを把握した上で使う方がいい. percentile returns an array instead of a list. That percentile value becomes the result of the median filter at position \(\v x\). SegmentFault 思否是中国领先的新一代开发者社区和专业的技术媒体。我们为中文开发者提供纯粹、高质的技术交流平台以及最前沿的技术行业动态，帮助更多的开发者获得认知和能力的提升。. The following fails, as expected:. Ideally, we need the nulls there -- can't turn them into 0s because that. Related articles. colon Dec 15, 2014 6:20 AM ( in response to pooja. 05 means that the fitted distribution is not significantly different to the observed distribution of the data. The 50th percentile for an array can be calculated in Numpy like so: numpy. 0729677997904314 The latter is an actual entry in the vector, while the former is a linear interpolation of two vector entries that border the percentile. axis: {int, tuple of int, None}, optional. Such speed-ups are not uncommon when using NumPy to replace Python loops where the inner loop is doing simple math on basic data-types. Pandas is an opensource library that allows to you perform data manipulation in Python. classification module¶ class pyspark. اگر از زبان خشک، بی روح و غیر تکنیکی متلب برای شبیه سازی ها و محاسبات علمی و عددیتان خسته شده اید و می خواهید با زبان پایتون که انعطاف پذیری و سرعت بیشتری نسبت به متلب دارد به انجام کارهای شبیه سازیتان بپردازید، پیشنهاد. percentile(x,70,interpolation="nearest") 2. 62 or less, while the median t(α) from the simulations is almost. So SQL Server Denali CTP3 added some new analytical functions: PERCENT_RANK, CUME_DIST, PERCENTILE_DISC and PERCENTILE_CONT. Python/Numpy (optional): Both Python development files (Python. To compute percentiles other than these default percentiles, use the PCTLPTS= and PCTLPRE= options in the OUTPUT statement. A numerical value that determines which values to ignore in the evaluation range for the function. nan と数値の比較をすると警告が出る. What is calculated. nonzero(a)[source] Return the indices of the elements that are non-zero. percentile(correct_array, 50). numpyもcrosstab時にsumする場合などに使うのでImportしておく; seabornまだ使ってない -> よく使うようになった. percentile(data,75,interpolation='higher') gives 2. This can be exceeded by structured arrays with a large number of columns. Alternative output array in which to place the. Universal functions (ufunc for universal functions) are functions that can be applied term-by-term to the elements of an array. ''' Build a tweet sentiment analyzer ''' from __future__ import print_function import six. standard_normal taken from open source projects. P is the desired percentile (25 or 75 for quartiles) and n is the number of values in the data set. The equations for the DS9 stretches can be found here and can be compared to the equations for our stretches provided in the astropy. rng_mrg import MRG_RandomStreams as RandomStreams import imdb datasets = {'imdb': (imdb. 0 / NFFT) * ((mag_frames) ** 2)) # Power Spectrum Filter Banks The final step to computing filter banks is applying triangular filters, typically 40 filters, nfilt = 40 on a Mel-scale to the power spectrum to extract frequency bands. The “INC” part of the function means to include 0% and 100% in the tallies. The following are code examples for showing how to use numpy. Thomas H has 11 jobs listed on their profile. 5\)-percentile) see a section in the Mathematical Tools section. For vectors, one can use instead the representations underlying coordinates, which allow one to use representations other than. This post is intended as a quick-start guide to getting a competitive score in the Higgs Boson Machine Learning Challenge, using just a bit of python and scikit-learn. Importing the NumPy module There are several ways to import NumPy. Percentile functions. matplotlibでどれだけめんどうかを把握した上で使う方がいい. For example the highest income value is 400,000 but 95th percentile is 20,000 only. The value of p must be between zero and one and must be constant for all input rows. 0 We see that the median height of US presidents is 182 cm, or just shy of six feet. When all-NaN slices are encountered a RuntimeWarning is raised and NaN is returned for that slice. 25, verbose=False, feature_selection='auto') ¶ Bases: object. 0 75th percentile: 183. approx_percentile (x, w, percentages) → array<[same. Axis or axes along which the percentiles are computed. Updated 2019-10-15 23:11:25 UTC. You can vote up the examples you like or vote down the ones you don't like. This is part 2 of a mega numpy tutorial. Pandas is also an elegant solution for time series data. 0‑cp38‑cp38‑win_amd64. Excel uses a slightly different algorithm to calculate percentiles and quartiles than you find in most statistics books. 5 * the IQR experimental analysis has shown that a higher/lower IQR might produce more accurate results. Here is a list of NumPy / SciPy APIs and its corresponding CuPy implementations. If one wants to use cache inside a class the recommended pattern is to cache a pure function and use the cached function inside your class, i. gandhi ) I have CreditOptic scores and I'm trying to get the. They portray a five-number graphical summary of the data Minimum, LQ, Median, UQ, Maximum. Thus if a same array stored as list will require more space as compared to arrays. feature_calculators. whl; NumPy, a fundamental package needed for scientific computing with Python. isscalar in that numpy. The whole point of numpy is to introduce a multidimensional array object for holding homogeneously-typed numerical data. A value of greater than 0. In python: import numpy as np n_samples = 30 desired_percentile = 90 x = np. *sigh* I don't know what it is, but it just wont let me ignore the blank cells in. A float number has a decimal in it. 25) = 30th data point. INC Finds a score given a percentile. This may help. load_data, imdb. Instead, it is common to import under the briefer name np:. It works elementwise for NumPy arrays. xLowerLeftCorner = p(-180. Combined statistical representations with distplot figure factory¶. reshape(shape, order='C') Returns an array containing the same data with a new shape. decay (float, optional) – A number between (0. Instead, I used numpy. nanpercentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=)¶. The result is equal to a specific column value. percentile() must be in [0,100] and I was providing them in [0,1]. 0 only allowed the array header to have a total size of 65535 bytes. With help from Intel, we have fixed the issues with SVML support (related issues #2938, #2998, #3006). Pandas provide an easy way to create, manipulate and wrangle the data. 9 the returned array is a read-only view instead of a copy as in previous NumPy versions. This is subtly different from numpy. To control this, I added the perc parameter, which sets the percentile of the shadow features' importances, the algorithm uses as the threshold. This is of course a useful tool for storing data, but it is also possible to manipulate large numbers of values without writing inefficient python loops. INC are new versions of PERCENTILE. Remove outliers using numpy. numpy で np. Numpy+Vanilla is a minimal distribution, which does not include any optimized BLAS libray or C runtime DLLs. One objective of Numba is having a seamless integration with NumPy. You can vote up the examples you like or vote down the ones you don't like. The average is taken over the flattened array by default, otherwise over the specified axis. Below is the list of python packages already installed with the Tensorflow environments. isscalar in that numpy. 075966046220879 np. MATLAB works differently, as it is primarily concerned with matrix operations. An integer is a plain number like 0, 10 or -2345. I don't want the test data [0. A normal distribution in statistics is distribution that is shaped like a bell curve. =PERCENTILE(IF(K4:AP4>0,K4:AP4),0. Files may be found at Sourceforge and pypi. 0 or omitted Ignore nested SUBTOTAL and AGGREGATE functions. statisticslectures. This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j : linear: i + (j - i) * fraction , where fraction is the fractional part of the index surrounded by i and j. Editado el 13 de junio de 2012: Añadidas funciones para crear arrays de NumPy a partir de listas y una nota sobre el peligro de la función empty. dev pytil (formerly known asChicken Turtle Util) is a Python utility library. ceil taken from open source projects. Y = prctile(X,p,vecdim) returns percentiles over the dimensions specified in the vector vecdim. If it is true, the Central_Meridian=180. In this case a dict containing the Lines making up the boxes, caps, fliers, medians, and whiskers is returned. Remove outliers using numpy. If neither of these is true, we cannot produce a confidence interval for a mean. By default direction is 0, which will search around the target. clip : bool, optional If `True` (default), values outside the [0:1] range are clipped to the [0:1] range. nonzero(a)[source] Return the indices of the elements that are non-zero. nanmean¶ numpy. 3 EE on Solaris 10. Efficient rolling statistics with NumPy. It makes the example better for everyone!. Related articles. 2 color scales produce a gradient from one color to another; 3 color scales use an additional color for 2 gradients. percentile(). PyTables uses these NumPy containers as in-memory buffers to push the I/O bandwith towards the platform limits. When pickling, both graph before and after the optimization are saved, including shared variables. The interface relies on Numpy arrays. The expression must evaluate to an exact or approximate numeric type, with no other data types allowed. The default is 90, for the 90th percentile. percentile (a, q, axis) 参数说明： a: 输入数组. 1 Ignore hidden rows, nested SUBTOTAL and AGGREGATE functions. This behavior is likely to change with revisions >= 1. isscalar returns False for a zero-dimensional array (e. EXC considers the K range 0 to 1 as exclusive. correlate numpy. Numpy is the core package for data analysis and scientific computing in python. 0‑cp38‑cp38‑win_amd64. average numpy. axis : axis along which we want to calculate the percentile value. DAX includes a few statistical aggregation functions, such as average, variance, and standard deviation. tensor as tensor from theano. INC with one difference: 0% and 100% are excluded. The port, which combines C# and C interfaces over a native C core, was done in such. Instead, I used numpy. Remember, python is a zero indexing language unlike R where indexing starts at one. isclose() function checks to see if two numbers are close in value. Refer to numpy. 5\)-percentile) see a section in the Mathematical Tools section. For example the highest income value is 400,000 but 95th percentile is 20,000 only. PERCENTILE remains in Excel for compatibility purpose only, you can ignore this Function. pyplot as plt import seaborn as sns from mpl_toolkits. Matlab/Octave (optional): The library is compatible with any Matlab from 2010 and Octave. percentile are changed to not handle NaN Median warns and returns nan when invalid values are encountered Similar to mean, median and percentile now emits a Runtime warning and returns NaN in slices where a NaN is present. In the formula, A1:A18 is the numbers you use, 0. In a nutshell this will flatten arr into a 1d array and convert the first element of each tuple, x[0], into a float during the process. array(1)), while this is True for quantities, since quantities cannot represent true numpy scalars. Select a blank cell that you want to place the result, enter this formula =PERCENTILE(IF(A1:A18,A1:A18),0. matplotlibでどれだけめんどうかを把握した上で使う方がいい. Utility functions to calculate percentiles and percent ranks in a JavaScript array. The function takes both an array of observations and a floating point value to specify the percentile to calculate in the range of 0 to 100. INC, PERCENTILE. absolute (numpy. matrix by default. 17 QUARTILE. Consider the ordered list {15, 20, 35, 40, 50, 55}, which contains six data values. The goal of this collection is to offer a quick reference for both old and new users but also to provide a set of exercises for those who teach. accuracy must be a value greater than zero and less than one, and it must be constant for all input rows. cPickle as pickle from collections import OrderedDict import sys import time import numpy import theano from theano import config import theano. 62 or less, while the median t(α) from the simulations is almost. I have fixed the example and made it clearer how the percentile values are calculated (so they can be debugged by the skeptical developers we should be). So SQL Server Denali CTP3 added some new analytical functions: PERCENT_RANK, CUME_DIST, PERCENTILE_DISC and PERCENTILE_CONT. The training is online and is constant in memory w. nth_percentile The percentile value. 0 is the result of seven months of work and contains a large number of bug fixes and new features, along with several changes with potential compatibility issues. This behavior is likely to change with revisions >= 1. Returns the qth percentile(s) of the array elements. feature_extraction. When set to True, the graph is reoptimized when being unpickled. reshape(shape, order='C') Returns an array containing the same data with a new shape. The fastest version (30-300 times) uses c directly but requires an array as input (with the double type, other data types are not yet supported):. 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: