Pandas Compare Two Rows

pyplot as plt import pandas as pd df. columns)) This will provide the unique column names which are contained in both the dataframes. Performing column level analysis is easy in pandas. tail — prints the last N rows of a DataFrame. I mentioned, in passing, that you may want to group by several columns, in which case the resulting pandas DataFrame ends up with a multi-index or. Combining Data Frames Pandas offers several methods to combine DataFrames, that can be separated into two approaches, which are concatenation and merging. In this video, I'll demonstrate the two key methods for finding and removing duplicate rows, as well as how to modify their behavior to suit your specific needs. Now, I need to merge them together based on a common column in the two data frames (df1 and df2) and also keep track of what row was in the the main data frame and not in the subset data frame. Quick Tip: Comparing two pandas dataframes and getting the differences Posted on January 3, 2019 January 3, 2019 by Eric D. of Columns and their types between the two excel files and whether number of rows are equal or not. At the end, it boils down to working with the method that is best suited to your needs. How to get the union of two MultiIndex DataFrames? Pandas - Merge two dataframes with different number of rows; different amount of rows after merging two dataframes with pandas; Fastest way to compare rows of two pandas dataframes? pandas outer product of two dataframes with same index; Pandas excel like countifs of two dataframes with. Next, we need to start jupyter. Symbol names vary with DB name; for WIKI (US stocks), they are the common ticker symbols, in some other cases (such as FSE) they can be a bit strange. shift(1) [/code]pandas. df [: 2] coverage name reports View Rows Where Coverage Is Greater Than 50 And Reports Less Than 4. The corresponding value in the pivot table is defined as the mean of these two original values. start <= repeats. Pandas is a popular Python library used for data science and analysis. A step-by-step Python code example that shows how to select Pandas DataFrame rows between two dates. Each row in a DataFrame is associated with an index, which is a label that uniquely identifies a row. If you want to manage paragraphs, table rows and a whole run with its style, you must use special tag syntax as explained in next chapter. 20 Dec 2017. Comparing two columns in two different rows. Comparing two Excel columns with Pandas and Numpy 3 minute read Having been asked multiple times if I can quickly compare two numeric columns from an excel file, I set up a small Jupyter notebook (and an R script) to show the intersection, the union and set differences of two columns. How to Get Unique Values from a Column in Pandas Data Frame? January 31, 2018 by cmdline Often while working with a big data frame in pandas, you might have a column with string/characters and you want to find the number of unique elements present in the column. Urgent Breaking News of Famous People in society Who Died Today somewhere in the World. Find the duplicate row in pandas: duplicated() function is used for find the duplicate rows of the dataframe in python pandas. import pandas as pd Use. As an extension to the existing RDD API, DataFrames features seamless integration with all big data tooling and infrastructure via Spark. Pandas Tutorial - Selecting Rows From a DataFrame Learn the various ways of selecting data from a DataFrame. Let's discuss all different ways of selecting multiple columns in a pandas DataFrame. DataFrame) (in that it prints out some stats, and lets you tweak how accurate matches have to be). I want to calculate the scipy. Sean Taylor recently alerted me to the fact that there wasn't an easy way to filter out duplicate rows in a pandas DataFrame. This takes less than a second on 10 Million rows on my laptop: Spearmanr on two pandas. sample (5) # random sample of rows df. tl;dr We benchmark several options to store Pandas DataFrames to disk. Compare two columns in pandas to make them match So I have two data frames consisting of 6 columns each containing numbers. csv file and compare to see if the first field of line 1 is the. The first argument to reader() is. For each group, head(. DataFrame( data, index, columns, dtype, copy) In the above example, two rows were dropped because those two contain the same label 0. Pandas Cheat Sheet — Python for Data Science Pandas is arguably the most important Python package for data science. Instead it seems to compare row-wise brutally. read_csv('train. This is a basic programming operation and I think pandas is way overkill for it. Difference of two columns in a pandas dataframe in python Difference of two Mathematical score is computed using simple – operator and stored in the new column namely Score_diff as shown below df1['Score_diff']=df1['Mathematics1_score'] - df1['Mathematics2_score'] print(df1). The tree is initialized with the contents of the XML file if given. 5 rows × 25 columns. Pandas DataFrame Exercises, Practice and Solution: Write a Pandas program to append a new row 'k' to DataFrame with given values for each column. equals¶ DataFrame. g [code]df['new coulmn'] = 1 df [/code]. If no, you have duplicate keys, yet unique rows, and need to decide which rows to save. From querying Google and SO, it seems like getting MySQL to do this transform is a bit of a pain. In this example lets see how to. The data is categorical, like this: var1 var2 0 1 1 0 0 2 0 1 0 2. If you want to learn the basics of SQL, you might like to checkout our SQL basics blogpost first. To drop one or more rows from a Pandas dataframe, we need to specify the row indexes that need to be dropped and axis=0 argument. I want to make an if statement with the values of two pandas data frames (the values I want to compare are in column 0): EDIT: First of all I wanted to check the number of times at which the value of df1 is greater than the value of df2. One solution to this problem is to grab even and odd rows separately and plot the data, which is quite complicated operation if types has more varieties e. A step-by-step Python code example that shows how to Iterate over rows in a DataFrame in Pandas. You should never modify something you are iterating over. Preliminaries. When we use parameterized queries, we use placeholders instead of directly writing the values into the statements. Let us use Pandas unique function to get the unique values of the column “year” >gapminder_years. According to NumPy's broadcasting rules (see Computation on Arrays: Broadcasting), subtraction between a two-dimensional array and one of its rows is applied row-wise. Merge, join, and concatenate¶. Pandas Tutorial - Selecting Rows From a DataFrame Learn the various ways of selecting data from a DataFrame. Thus, they bound with FID_1 and NEAR_FID columns. The words “merge” and “join” are used relatively interchangeably in Pandas and other languages, namely SQL and R. Generic Public Class DinoComparer Implements IComparer(Of String) Public Function Compare(ByVal x As String, _ ByVal y As String) As Integer _ Implements IComparer(Of String). You should never modify something you are iterating over. NaN print df 2008 2009 Asia NaN NaN China 20080 20090 India 20080 20090 Europe NaN NaN France 20080 20090 Hungary 20080 20090. It doesn’t enumerate rows (which is a default index in pandas). A Series is a one-dimensional array that can hold any value type - This is not necessarily the case but a DataFrame column may be treated as a Series. The format string supports the most common substitutions found in the strftime() function from the standard C library plus two new substitutions, %f and %J. diff¶ DataFrame. Group 3 alphanumeric) with two characters, here you need to specify the length of the variable for Stata. duplicate() function. Every variable in Python is an object. You want to calculate sum of of values of Column_3, based on unique combination of Column_1 and Column_2. SQLite Python parameterized queries. Compare If x Is Nothing Then If y Is Nothing Then ' If x is Nothing and y is Nothing, they're ' equal. The tree is initialized with the contents of the XML file if given. If you only need to check whether or not two dataframes are exactly the same, you should look at the testing capabilities within Pandas and Numpy:. Parameters: values: iterable, Series, DataFrame or dict. You can merge two data frames using a column column. I have two data frames df1 and df2 and I would like to merge them into a single data frame. iloc[, ], which is sure to be a source of confusion for R users. A step-by-step Python code example that shows how to select Pandas DataFrame rows between two dates. If we have the file in another directory we have to remember to add the full path to the file. Boyce defined the Boyce-Codd normal form (BCNF) in 1974. Delete the duplicate rows from the original table. DataComPy is a package to compare two Pandas DataFrames. head() method displays the first 5 rows by default. RIP Tutorial. If you have read the post in this series on NumPy , you can think of it as a numpy array with labelled elements. A series is a one-dimensional data type where each element is labelled. “Always and never are two words you should always remember never to use. index[0:5] is required instead of 0:5 (without df. My business problem is that I have two Excel files that are structured similarly but have different data and I would. You just saw how to apply an IF condition in pandas DataFrame. Similar to a left join, except all rows from the right DataFrame are kept, while rows from the left DataFrame without matching join key(s) values are discarded. Pandas merge function provides functionality similar to database joins. Setup a private space for you and your coworkers to ask questions and share information. Learning pandas - PDF Books. How to plot date and time in pandas. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package). Note that Spark DataFrame doesn’t have an index. The result will only be true at a location if all the labels match. 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. Pandas – Python Data Analysis Library. df_a == df_b also performs row-wise comparison but if the indices of those 2 DataFrames were not exactly the same (in values and orders), it will throw ValueError: Can only compare identically-labeled DataFrame objects. Pandas - Python Data Analysis Library. pandas has methods useful for inspecting data values. You can find these by opening Excel, clicking File then Open, and selecting two workbooks to compare from the menu that appears. You can just subscript the columns: df = df[df. Country field to the Rows area. Pandas and Numpy are two packages that are core to a lot of data analysis. All gists Back to GitHub. In comparison with SAS PROC COMPARE which can operate on datasets that are on disk, this could be a constraint if you're using very large dataframes. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. The format string supports the most common substitutions found in the strftime() function from the standard C library plus two new substitutions, %f and %J. If you want to manage paragraphs, table rows and a whole run with its style, you must use special tag syntax as explained in next chapter. Get the list of column headers or column name in python pandas In this tutorial we will learn how to get the list of column headers or column name in python pandas using list() function. difference (self, other, sort=None) [source] ¶ Return a new Index with elements from the index that are not in other. For example, to retrieve the ninth column vector of the built-in data set mtcars , we write mtcars[[9]]. Now, I need to merge them together based on a common column in the two data frames (df1 and df2) and also keep track of what row was in the the main data frame and not in the subset data frame. There are times when working with different pandas dataframes that you might need to get the data that is ‘different’ between the two dataframes (i. zeros¶ numpy. You can find these by opening Excel, clicking File then Open, and selecting two workbooks to compare from the menu that appears. ElementTree Objects¶ class xml. Python Pandas : compare two data-frames along one column and return content of rows of both data frames in another data frame Filter dataframe rows if value in column is in a set list of values pandas how to count the number of rows whose column values add up to a threshold. There are two pandas dataframes I have which I would like to combine with a rule. • Often data come naturally in the form of a table, e. DataFrame(index=['Asia','China','India','Europe','France','Hungary']) df[2008]=20080 df[2009]=20090 df. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package). To calculate the numerator of τ , we compare all possible pairs in the dataset and count number of concordant pairs; 6 in this case:. apply(): Apply a function to each row/column… Python Pandas : How to create DataFrame from dictionary ? Pandas : 6 Different ways to iterate over rows in a… Pandas : skip rows. read_csv('train. DB names can be all the free ones listed on the Quandl website. You might be wondering why there need to be so many articles on selecting subsets of data. It mean, this row/column is holding null. Learning pandas - PDF Books. It is a vector that contains data of the same type as linear memory. head — prints the first N rows of a DataFrame. Displayed below are the first 5 rows of the DataFrame we imported (to see the last n rows use. Pandas Cheat Sheet — Python for Data Science Pandas is arguably the most important Python package for data science. There are a ton of things we can do with DataFrames, and you can find some great examples of merges, joins, and concatenations here. table library frustrating at times, I’m finding my way around and finding most things work quite well. Pandas DataFrame Exercises, Practice and Solution: Write a Pandas program to iterate over rows in a DataFrame. , spreadsheet, which need a two-dimensional array. Compare two dataframes. Suppose you have a dataset containing credit card transactions, including: the date of the transaction; the credit card number; the type of the expense. pandas: Adding a column to a DataFrame (based on another DataFrame) Nathan and I have been working on the Titanic Kaggle problem using the pandas data analysis library and one thing we wanted to do was add a column to a DataFrame indicating if someone survived. read_csv("ign. Also it gives an intuitive way to compare the dataframes and find the rows which are common or uncommon between two dataframes. SQLite Python parameterized queries. SD is a data. We can make sure our new data frame contains row corresponding only the two years specified in the list. GitHub Gist: instantly share code, notes, and snippets. [code]from itertools import izip_longest import xlrd rb1 = xlrd. It is the first time I use pandas and I do not really know how to deal with my problematic. 7 series, we cover the notion of column manipulation with CSV files. I have two data frames df1 and df2 and I would like to merge them into a single data frame. In the first example of this Pandas read CSV tutorial we will just use read_csv to load CSV to dataframe that is in the same directory as the script. Compare the No. ElementTree Objects¶ class xml. Varun March 9, 2019 Pandas : 6 Different ways to iterate over rows in a Dataframe & Update while iterating row by row 2019-03-09T09:08:59+05:30 Pandas, Python No Comment In this article we will discuss six different techniques to iterate over a dataframe row by row. Count the number of unique values by using a filter You can use the Advanced Filter dialog box to extract the unique values from a column of data and paste them to a new location. Helpful Python Code Snippets for Data Exploration in Pandas #Code snippets for Pandas import pandas as pd # skip the first two rows of data # randomly sample a DataFrame train = df. This article shows the python / pandas equivalent of SQL join. Where colid refers to a named range you would create elsewhere within the workbook comprising two adjacent columns with multiple rows: the first column containing the numbers 1 to n corresponding to the COLUMN() number, the second containing the letters A - ZZ, or however many column references you wish to accommodate. Now we will concern ourselves with parameterized queries. head — prints the first N rows of a DataFrame. Download with Google Download with Facebook or download with email. Apply a Function to Columns/Rows. df1 has 50000 rows and df2 has 150000 rows. Populate column based on previous row with a twist. Common uses include membership testing, removing duplicates from a sequence, and computing standard math operations on sets such as intersection, union, difference, and symmetric difference. Pandas is one of those packages, and makes importing and analyzing data much easier. diff (self, periods=1, axis=0) [source] ¶ First discrete difference of element. This function allows two Series or DataFrames to be compared against each other to see if they have the same shape and elements. See the Package overview for more detail about what’s in the library. Learn how to slice and dice, select and perform commonly used operations on DataFrames. concat ([df_a Merge two dataframes with both the left and right dataframes. You can merge two data frames using a column column. 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. 5 rows × 25 columns. import os import difflib f=open. If you have read the post in this series on NumPy , you can think of it as a numpy array with labelled elements. Once you've opened one of the workbooks, you can click on the View tab in the top-center of the window. Parameters: values: iterable, Series, DataFrame or dict. [Pandas] Difference between two datetime columns I've got a data frame in which there are two columns with dates in form of string. In this post, focused on learning python programming, we’ll. To keep things simple I use the same tables as above except the right able is the table above stacked on itself. We load it into BeautifulSoup and parse it, returning a pandas data frame of the contents. txt file to a pandas dataframe. So the result will be. , spreadsheet, which need a two-dimensional array. Use groupby(). read_csv('amis. There are several ways to count unique values among duplicates. You can vote up the examples you like or vote down the ones you don't like. Performing column level analysis is easy in pandas. Python Pandas - Comparison with SQL. As Arrow Arrays are always nullable, you can supply an optional mask using the mask parameter to mark all null-entries. Learn more about Teams. ) It is a plot of the true positive rate against the false positive rate for the different possible cutpoints of a diagnostic test. If you want to learn the basics of SQL, you might like to checkout our SQL basics blogpost first. "This grouped variable is now a GroupBy object. Pandas is one of those packages, and makes importing and analyzing data much easier. As an extension to the existing RDD API, DataFrames features seamless integration with all big data tooling and infrastructure via Spark. A single column or row in a Pandas DataFrame is a Pandas series — a one-dimensional array with axis labels. They are extracted from open source Python projects. SQLite Python parameterized queries. The first one is a grouped based on the nearness (spatial near) of the second dataframe. How to compare two different formulations. Using Power Query I was able to sort the data and persist the order after sort using an index column. Variables and Types. The words “merge” and “join” are used relatively interchangeably in Pandas and other languages, namely SQL and R. Here is what we are trying to do as shown in Excel: As you can see, we added a SUM(G2:G16) in row 17 in each of the columns to get totals by month. So the result will be. Here’s the first, very simple, Pandas read_csv example: df = pd. Labels need not be unique but must be a hashable type. [code]from itertools import izip_longest import xlrd rb1 = xlrd. Filtering rows of a DataFrame is an almost mandatory task for Data Analysis with Python. Python Pandas - Comparison with SQL. unique() array([1952, 2007]) 5. This is useful when cleaning up data - converting formats, altering values etc. index command above showing the index is made up of strings. In this video, I'll demonstrate the two key methods for finding and removing duplicate rows, as well as how to modify their behavior to suit your specific needs. count() Returns the number of rows in the DataFrame. For more information, see Create and Work with Tables or watch Tables and Categorical Arrays. Pandas merge function provides functionality similar to database joins. like this: in file1. equals¶ DataFrame. Reading from a. If you want to learn the basics of SQL, you might like to checkout our SQL basics blogpost first. Using Power Query I was able to sort the data and persist the order after sort using an index column. Calculates the difference of a Series element compared with another element in the Series (default is element in previous row). Filter pandas dataframe by rows position and column names Here we are selecting first five rows of two columns named origin and dest. It contains high-level data structures and manipulation tools designed to make data analysis fast and easy. Data Frame Column Vector We reference a data frame column with the double square bracket "[[]]" operator. How to Select Rows of Pandas Dataframe Based on Values NOT in a list?. start <= repeats. In our mini example, (4,6) and (5,9) in rows d and e is a concordant pair. Data Science: Performance of Python vs Pandas vs Numpy July 15, 2017 April 9, 2018 Lucas KM Tips and Tricks Note: this is updated version of original post from 15 July 2017. Here, axis=0 argument specifies we want to drop rows instead of dropping columns. Python Pandas - Comparison with SQL. Regular Expression Syntax¶ A regular expression (or RE) specifies a set of strings that matches it; the functions in this module let you check if a particular string matches a given regular expression (or if a given regular expression matches a particular string, which comes down to the same thing). Create a simple two dimensional array. The elements in x are sorted into 10 equally spaced bins along the x-axis between the minimum and maximum values of x. I'll also explain the. This function allows two Series or DataFrames to be compared against each other to see if they have the same shape and elements. xlsx') sheet1 = rb1. new-actor, new-actress and teen-actors etc. I would like to produce a new dataframe. You checked out a dataset of Netflix user ratings and grouped the rows by the release year of the movie to generate the following figure: This was achieved via grouping by a single column. Let us consider a toy example to illustrate this. For example below, in R, if the middle argument is 2, the function is applied to columns, while if it is 1, it is applied to rows. Python is completely object oriented, and not "statically typed". csv and file2. A series is a one-dimensional data type where each element is labelled. Create a pandas column with a for loop. Here are a couple of examples. concat() function joins data on index labels (countries, in our case), not sequence, so this won’t pose an issue during concatenation. Have you ever been confused about the "right" way to select rows and columns from a DataFrame? pandas gives you an incredible number of options for doing so, but in this video, I'll outline the. Parameters: values: iterable, Series, DataFrame or dict. Learn how I did it!. A step-by-step Python code example that shows how to select Pandas DataFrame rows between two dates. equals(Pandas. apply to send a single column to a function. Variables and Types. In comparison with SAS PROC COMPARE which can operate on datasets that are on disk, this could be a constraint if you're using very large dataframes. Specifically for Python, DataFrames come with the Pandas library, and they are defined as a two-dimensional labeled data structures with columns of potentially different types. Missing Count The number of missing data values. tail — prints the last N rows of a DataFrame. start <= repeats. pandas has methods useful for inspecting data values. number_rows = len ( df. sheet_by_index(0. I want to compare this file with db. Lets see with an example. 5 , but this same approach should work with Python 2. The rows in the two data frames that match on the specified columns are extracted, and joined together. This code imports the openpyxl module, as well as the pprint module that you’ll use to print the final county data. Here’s the first, very simple, Pandas read_csv example: df = pd. Next, let’s get some totals and other values for each month. read_table("blast") cluster=pandas. value # TODO: Open a new text file and write the contents of countyData to it. Pandas is one of those packages and makes importing and (series), 2 for two dimension it is compared by multiplying rows and columns returned by the. 5 seconds for 10 million records) filter data (>10x-50x faster with sqlite. We can see that just first two rows have new names as we intended. [Pandas] Difference between two datetime columns I've got a data frame in which there are two columns with dates in form of string. This page is based on a Jupyter/IPython Notebook: download the original. Pandas DataFrame Exercises, Practice and Solution: Write a Pandas program to iterate over rows in a DataFrame. for row in rows: print "{} {} {}". If we have the file in another directory we have to remember to add the full path to the file. It doesn’t enumerate rows (which is a default index in pandas). Specifically for Python, DataFrames come with the Pandas library, and they are defined as a two-dimensional labeled data structures with columns of potentially different types. hist displays bins as rectangles, such that the height of each rectangle indicates the number of elements in the bin. Two-Dimensional Arrays • Arrays that we have consider up to now are one-dimensional arrays, a single line of elements. RIP Tutorial. difference (self, other, sort=None) [source] ¶ Return a new Index with elements from the index that are not in other. Here, axis=0 argument specifies we want to drop rows instead of dropping columns. shape we can use dataframe. equals , This function allows two Series or DataFrames to be compared against each other to see if they have the same shape and elements. A step-by-step Python code example that shows how to Iterate over rows in a DataFrame in Pandas. In this array there are n = 5 rows, m = 6 columns, and the element with row index i and column index j is calculated by the formula a[i][j] = i * j. Python is a valuable tool in the tool chest of many data scientists. Skipping the first two rows (including the header) Get unlimited access to the best stories on Medium — and support writers while you. How to compare two rows of two pandas series? (Python) - Codedump. For this, we use the csv module. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Here I am going to introduce couple of more advance tricks. I have a pandas dataframe with 21 columns. concat() function joins data on index labels (countries, in our case), not sequence, so this won’t pose an issue during concatenation. df_new = pd. hist displays bins as rectangles, such that the height of each rectangle indicates the number of elements in the bin. How to Compare data in Two Excel Spreadsheets. table library frustrating at times, I’m finding my way around and finding most things work quite well. How to Get Unique Values from a Column in Pandas Data Frame? January 31, 2018 by cmdline Often while working with a big data frame in pandas, you might have a column with string/characters and you want to find the number of unique elements present in the column. As part of my continued exploration of pandas, I am going to walk through a real world example of how to use pandas to automate a process that could be very difficult to do in Excel. I am using a panda's dataframe and I am doing filtering and some calculations per column and per row. Python Pandas : compare two data-frames along one column and return content of rows of both data frames in another data frame Filter dataframe rows if value in column is in a set list of values pandas how to count the number of rows whose column values add up to a threshold. how to column bind two data frames in python pandas. Customer or Disqualified Prospect) and the. Let's say that you want to filter the rows of a DataFrame by multiple conditions. open_workbook('file1. We can use the same drop function in Pandas. Under the hood, a Dask Dataframe consists of many pandas DataFrames A question that arises is, how can data that does not fit in memory while using Pandas, fit in memory when using Dask. SUBSCRIBE to learn data science. The corresponding value in the pivot table is defined as the mean of these two original values. 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: