Python Split Csv Column

Hi anand, According to your description, I think you want to read the specific columns from. Let us get started with an example from a real world data set. I would like to study a range of data using the same technique in ArcMAP (it will take too much time to do it one by one ;) !). Accessing pandas dataframe columns, rows, and cells At this point you know how to load CSV data in Python. Python - Read and split lines from text file into indexes. And then split each line by the delimiter (commas I am assuming but easy enough to switch to tabs). CSV (Comma Separated Values) is a most common file format that is widely supported by many platforms and applications. csv (excel). Exchanging information through text files is the standard way to share info between programs and one of the most popular formats for transferring data in the CSV format. Pandas split CSV into multiple CSV's (or DataFrames) by a column To split one CSV by The_evil_column colum? Adding new column to existing DataFrame in Python. 3) September 2018. Alright, without further to do here is the module to date. How do you remove a column of a. (6 replies) Hey, gang, I've got a problem here that I'm sure a handful of you will know how to solve. csv') column2 = data. Pandas is a library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. CSV(Comma Separated Values) files are used to store a large number of variables or data. Week 2 Assignment 2 - Pandas Introduction All questions are weighted the same in this assignment. In addition, Python’s built-in string classes support the sequence type methods described in the Sequence Types — str, unicode, list, tuple, bytearray, buffer, xrange section, and also the string-specific methods described in the. If you require more examples, there are countless sources on the Internet. It should work fine under 2. XGBoost binary buffer file. While it would be pretty straightforward to load the data from these CSV files into a database, there might be times when you don’t have access to a database server and/or you don’t want to go through the hassle of setting up a server. Double quotes are used to wrap values that contain special characters such as commas, double quotes, new lines, etc. Delimitator - Specifies the delimitator in the CSV file. Hey, Scripting Guy! I love comma-separated value (CSV) files. you have to specify the csv_filename and the column_header_name that has the urls to be downloaded. Description. to_csv - Write DataFrame to a comma-separated values (csv) file. Often while working with pandas dataframe you might have a column with categorical variables, string/characters, and you want to find the frequency counts of each unique elements present in the column. Python Pandas : How to get column and row names in DataFrame Select Rows & Columns by Name or Index in DataFrame using loc & iloc | Python Pandas Pandas : Find duplicate rows in a Dataframe based on all or selected columns using DataFrame. You cannot tell it’s completely wrong, but it would be better to split these values into ‘gender’ and ‘age’ columns. Getting Unique values from a column in Pandas dataframe; Split a column in Pandas dataframe and get part of it; Formatting integer column of Dataframe in Pandas; Split a text column into two columns in Pandas DataFrame; Create a new column in Pandas DataFrame based on the existing columns; Python | Change column names and row indexes in Pandas. There are approximately 1,800 rows, including the header row, and 9 columns in the file. Simply upload your. Java 7 is currently the minimum supported version. {"categories":[{"categoryid":387,"name":"app-accessibility","summary":"The app-accessibility category contains packages which help with accessibility (for example. DictWriter class operates like a regular writer but maps Python dictionaries into CSV rows. How do I select multiple rows and columns from a. The problem is that I need to get this CSV data into individual rows in order to analyze it more. The numbers on the left are the indexes. Dot Net Perls C# Array C# List 2D Array async Console Constructor DataTable DateTime DateTime Format Dictionary Enum File For Foreach IEnumerable If IndexOf int. The above code produces a Dataframe with latitude and longitude columns that you can map with any Geographic visualisation tool of your choice. CSV is cardware. Pandas couldn’t parse the file, as it was expecting commas, not. To pull information from CSV files you use loop and split methods to get the data from individual columns. Corey Schafer 320,646 views. These two excel files should contain data from input. With this site we try to show you the most common use-cases covered by the old and new style string formatting API with practical examples. " While you can also just simply use Python's split() function, to separate lines and data within each line, the CSV module can also be used to make things easy. First, if it is a list of strings, you may simply use join this way:. Build Fix problem building on OSF1 because the compiler only accepted preprocessor directives that start in column 1. Securely split a CSV file - perfect for private data How to open a large CSV file How to reorder and/or remove columns in a CSV file How to detect and remove duplicate rows from a CSV file CSV Splitter How to split a csv file by rows How to Split a CSV in Python How to split a CSV file in Google Drive. To do this we use Python slicing sintaxis by accessing. Split-Apply-Combine¶ Many statistical summaries are in the form of split along some property, then apply a funciton to each subgroup and finally combine the results into some object. We show the output of the program. Note: I’ve commented out this line of code so it does not run. Follow these steps to split the data from column A into a "Last Name" column and a "First Name" column. Python CSV Files: Reading and Writing - DZone Big Data / Big. Like you need to export or import spreadsheets. csv of course) which contains several columns each with a column header. OneHotEncoder is going to split the data into different columns, each column represent the existence of one value using 0 and 1. This example shows how to perform aggregate computations such as Sum, Average, Min, and Max on the columns of a. writer() module to write data into csv files. 0, the string split takes 1. The train-test split is a simple resampling method that can be used to evaluate a machine learning algorithm. CSV format was used for many years prior to attempts to describe the format in a standardized way in RFC 41. The final code will not deal with open file for reading nor writing. Pandas Cheat Sheet for Data Science in Python A quick guide to the basics of the Python data analysis library Pandas, including code samples. 7 - I’m pretty sure that it will work in Python 3 as well after I switch out the built-in IO functions for the Python csv module:. com covers most of the content of the book. So how can we easily split the large data file containing expense items for all the MPs into separate files containing expense items for each individual MP? Here’s one way using a handy little R script in RStudio… Load the full expenses data CSV file into RStudio (for example, calling the dataframe it is loaded into mpExpenses2012. Split Column > By Delimiter parses a text value into two or more columns according to a common character. My file includes two columns, but on the step "Column customization" they are combined into one column for some unknown reason and I dont know how to split them. df file_name 1 1_jan_2018. Double quotes in a column value should be replaced with a pair of double quotes (This is Excel's approach). If you’d like to run the script, you’ll need: data from the Analytics Edge competition. The following Python program converts our test CSV file to a CSV file that uses tabs as a value separator and that has all values quoted. Thanks for your cooperation and help. Contribute to datacamp/courses-kaggle-python-machine-learning development by creating an account on GitHub. With the file open, create a new csv. Creating DataFrames from CSV (comma-separated value) files is made extremely simple with the read_csv() function in Pandas, once you know the path to your file. In particular, the fundedDate needs to be transformed to a Python date object and the raisedAmt needs to be converted to an integer. Python Data Products Specialization: Course 1: Basic Data Processing… Summary of concepts •Understand the methods. Let say that your input data is in CSV file and you expect output as SQL insert. It just means in the case of the example, someone has made a module called "toolbox" where they've placed the csv_splitter file (presumably with other "tools" for their program). So, is there a way to make excel go through all of the cells in a single column and break up the values into multiple columns, appending cells to the end of. Write a Python program that finds the city with the largest population in pop. txt 1,Python,35,PyCharm 2,Java,28,IntelliJ 3,Javascript,15,WebStorm And we want. Then after saved, change the extension to. csv file so I can fit it into Excel, resulting in 20 columns by 700 rows. Opencsv is an easy-to-use CSV (comma-separated values) parser library for Java. I need these to be split across columns. disk) to avoid being constrained by memory size. I am trying to create a new csv file using python. Once loaded, Pandas also provides tools to explore and better understand your dataset. Well organized and easy to understand Web building tutorials with lots of examples of how to use HTML, CSS, JavaScript, SQL, PHP, Python, Bootstrap, Java and XML. Pandas is a library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. The problem is that when I opened the excel file I have all the data in only one column, split by the comma. csv file from current folder and then slices it to n parts and adds a first column, if provided. It has only one column with number of strings. The train-test split is a simple resampling method that can be used to evaluate a machine learning algorithm. This tutorial will give a detailed introduction to CSV's and the modules and classes available for reading and writing data to CSV files. The data will be loaded using Python Pandas, a data analysis module. train_test_split. You can do this on Cases_Guinea, for example, using Cases_Guinea. Split up CSV column contents into multiple columns I am trying to tie another piece into my existing Python program. @Jazz193 the "from toolbox import csv_splitter" is just an example. More about the CSV format. The file data contains comma separated values (csv). Alright, without further to do here is the module to date. Create your free Platform account to download our ready-to-use ActivePython or customize Python with any packages you require. The network has a training phase. , data is aligned in a tabular fashion in rows and columns. Easiest to use pandas: [code]>>> import pandas as pd >>> data = pd. Sorting a CSV File Using Python. Reading CSV files using Python 3 is what you will learn in this article. If you require more examples, there are countless sources on the Internet. However, it can also be separated by using other characters such as a “|” or a “tab”. Python | Pandas Split strings into two List/Columns using str. read_csv('filename. I am a data scientist with a decade of experience applying statistical learning, artificial intelligence, and software engineering to political, social, and humanitarian efforts -- from election monitoring to disaster relief. The XGBoost python module is able to load data from: LibSVM text format file. I am new to Python and can't seem to figure it out, even with all of the help out there. There’s also the inverse operation, taking our DictObj’s. >>> import csv Next, I'll create a variable called "reader" which does the following: Calls the csv. Python Data Products Specialization: Course 1: Basic Data Processing… Summary of concepts •Understand the methods. read_csv in pandas. Numpy_Example_List_With_Doc has these examples interleaved with the built-in documentation, but is not as regularly updated as this page. Now it is easy to merge csv into a database table by using the new Generate MERGE feature. Next I tried a run of each method using 500,000 integers concatenated into a string 2,821 kB long. I have a text file with hundreds of lines and 10 columns of data separated by commas. Rainbow CSV has content-based csv/tsv autodetection mechanism. csv (excel). csv") If (success <> 1) Then outFile. How do I split a column of a csv file in excel using python 3. Use csv module from Python's standard library. After all, a CSV is one of the easier file formats to parse (as seen below), and Python is great for working with strings: Name,Age,Favorite Color Jeremy,25,Blue Ally,41,Magenta Jasmine,29,Aqua. Lots of examples of ways to use one of the most versatile data structures in the whole Python data analysis stack. csv(file = "result1", sep= " "). Every major programming language has support for CSV file I/O (input/output). Numpy_Example_List_With_Doc has these examples interleaved with the built-in documentation, but is not as regularly updated as this page. Python tips - How to easily convert a list to a string for display There are a few useful tips to convert a Python list (or any other iterable such as a tuple) to a string for display. Expand the splitted strings into separate columns. Just right-click the output of the module to generate the code needed to access the data directly from Python or a Jupyter notebook. Accessing pandas dataframe columns, rows, and cells At this point you know how to load CSV data in Python. expand: bool, default False. Create a new text file in your favorite editor and give it a sensible name, for instance new_attendees. Python CSV Files: Reading and Writing - DZone Big Data / Big. Disclaimer: this will still only work if the last column is the multi-valued one, but a few loops and if/elses could resolve that if anyone wanted. In one file, delete everything below this line. A csv file, a comma-separated values (CSV) file, storing numerical and text values in a text file. A sequence should be given if the object uses MultiIndex. py helps analyze new PYTHONDUMPREFS output. csv') >>> data. In the Excel Browse or Comma-Separated Values Browse dialog box, browse for or type a path to the file that you want to query. When the vectors are created from R, one should not worry much as they will be exposed as they should by rpy2. The image has a sample column, however the data is not consistent. Python string method split() returns a list of all the words in the string, using str as the separator (splits on all whitespace if left unspecified), optionally limiting the number of splits to num. You need to use the split method to get data from specified columns. How to read and write a CSV files. Introduction Which algorithm do you use for object detection tasks? I have tried out quite a few of them in my quest to build. The task to process smaller pieces of data will deal with CSV via csv. Data in each CSV file is different and describes a particular. reader() module. An xls is easily read with xlrd, but xlrd nor any other Python library (as far as I could find) supports xlsx, so instead I'm using xlsx2csv to convert to csv and then reading values from that. Comma-separated value data is likely the structured data format that we’re all most familiar with, due to CSV being easily-consumed by spreadsheet applications. Related course Complete Python Bootcamp: Go from zero to hero in Python. Filed Under: Pandas DataFrame, Python Tips Tagged With: get part of column in Pandas, Pandas Data Frame, Split Column Names of Pandas Dataframe Subscribe to Blog via Email Enter your email address to subscribe to this blog and receive notifications of new posts by email. An xls is easily read with xlrd, but xlrd nor any other Python library (as far as I could find) supports xlsx, so instead I'm using xlsx2csv to convert to csv and then reading values from that. We show the output of the program. I want to split this one column into 2 columns at the character \. Column storage allows for efficiently querying tables with a large number of columns. split REGEX, STRING will split the STRING at every match of the REGEX. If False do not print fields for index names. My data is coming from a CSV, which should be visualized in Tableau. Quit End If ' Display the contents of the 3rd column (i. csv') print (df). 7 support as well. uniCSVed, is an Unicode compatible CSV editor. select column in csv file in Python. Pandas’ value_counts() easily let you get the frequency counts. field_size_limit – return maximum. The CSV module explicitly exists to handle this task, making it much easier to deal with CSV formatted files. There can be other types of values as the delimiter, but the most standard is the comma. encoding: str, optional. The file has many columns for real estate sales such as date, location and price. Corey Schafer 320,646 views. This package is fully compatible with Python >=3. In this Pandas with Python tutorial video with sample code, we cover some of the quick and basic operations that we can perform on our data. csv (excel). How to Convert CSV to Excel 2013 Format (XLSX) There are plenty of apps, and quite a few online services, available online for the simple task of converting the standard CSV (comma separated value) format into the regular Excel formatting than you know and love. csv file that has around 700 columns, and 20 rows. dat")) for row in reader: print row i want the first element of the row be the key for the dictionary so that if i access the dictionary again using the key i'll be able to get the different of the rows of that dictionary. The following Python program converts our test CSV file to a CSV file that uses tabs as a value separator and that has all values quoted. csv file? I have a. There's no sign up, no payment, and no account necessary. Stack Exchange Network. Calculate cumulative product and cumulative sum of DataFrame Columns in Pandas ; How to create series using NumPy functions in Pandas? Get cell value from a Pandas DataFrame row; How to create a pandas Series using lists and dictionaries? Find n-smallest and n-largest values from DataFrame for a particular Column in Pandas. We open our portfolio file, display. pandas read_csv converting mixed types columns as string Tag: python-3. The most common formats are CSV (Comma Separated Values) and tab delimited text. Many systems and processes today already convert their data into CSV format for file outputs to other systems, human-friendly reports, and other needs. frequency 1,10 2,30 3,20 4,70. Hey, Scripting Guy! I have a CSV file from which I need only two of eight columns. SFrame (data=list(), format='auto') ¶. Definitely, the fixed width of columns is something very different in principle. read() Then I didn't managed to print the file, because i obtained this message: <_csv. iloc[:,1] [/code]'iloc' is used to slice the dataframe by column indices. Generating SQL inserts from csv data. split() throws a FutureWarning when it encounters a zero-length match. The so-called CSV (Comma Separated Values) format is the most common import and export format for spreadsheets and databases. To pull information from CSV files you use loop and split methods to get the data from individual columns. On the left column, click on the Edit Column button and add the name Number in the ColumnName field. 7 series, we cover the notion of column manipulation with CSV files. However, in this case you want it to split by an underscore. I aim to pass the merged CSV file to R for plotting. 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. This is due to their flexibility and cross language support. simpleString , except that top level struct type can omit the struct<> and atomic types use typeName() as their format, e. It allows programmers to say, "write this data in the format preferred by Excel," or "read data from this file which was generated by Excel," without knowing the precise details of the CSV format used by Excel. read_csv('test. It should work fine under 2. Parse KeyValuePair Keywords Lambda LINQ Path Process Property Random Reflection Regex Replace Sort Split Static String Switch string. How to Set Dependent Variables and Independent Variables (iloc example) in Python by admin on April 11, 2017 with 2 Comments Say you have imported your CSV data into python as "Dataset", and you want to split dependent variables and the independent variables. field_size_limit - return maximum. python -c "import csv,sys; print '\n'. The max I have done till now is to use text-to-columns to split the csv column in multiple columns. A sequence should be given if the object uses MultiIndex. In this example, we can tell the baby_names. to_csv - Write DataFrame to a comma-separated values (csv) file. You'll find docs on that if you do a quick search. CSV spreadsheet files are suitable for storing tabular data in a relatively portable way. Column storage allows for efficiently querying tables with a large number of columns. Active 7 years, 7 months ago. For example to split superuser. writer for writing Dialects option correspond to prede ned formats ’excel’ for excel output without needing to know the separator and quote characters. Java 7 is currently the minimum supported version. How do I select multiple rows and columns from a. How to use Split in Python At some point, you may need to break a large string down into smaller chunks, or strings. CSV is cardware. Let us get started with an example from a real world data set. csv file? The columns after the first column are dynamic. OneHotEncoder is going to split the data into different columns, each column represent the existence of one value using 0 and 1. There are a few good reasons to use the CSV module here: The csv module makes it clear what you’re doing to anyone reading your code. To read/write data, you need to loop through rows of the CSV. head() col1 col2 0 Arizona 373 1 California 371 2 Colorado 453 >. Split timestamp column into two new columns in CSV using python and pandas Tag: python , csv , numpy , pandas , itertools I have a large CSV file with over 210000 rows. csv") define the data you want to add color=['red' , 'blue' , 'green. Split a column by delimiter. The script below does just that however, the columns data is from one row. If you know that your actual case IS the CSV file with a single column, and you will want to add more columns later, you can still use the csv. Decision trees in python with scikit-learn and pandas. Background: I'm extracting values from a file which is sometimes an xls and sometimes an xlsx file. Hi All, I have a file of received items in the company. txt file with 3 or 4 rows and columns of data. Set the Data Type as Int32. Reading CSV files using Python 3 is what you will learn in this article. The CSV module explicitly exists to handle this task, making it much easier to deal with CSV formatted files. Splitting a column with. select column in csv file in Python. DictWriter class operates like a regular writer but maps Python dictionaries into CSV rows. Even though the name is Comma Separated Values, they can be separated by anything. csv A memory-conservative solution for large files that iterates through the file a line at a time unlike the above approach that loads the contents of the file into memory via a list. Often I've needed to format columns of text going into email messages. Next, a newline character is added to the end of the string. The data in SFrame is stored column-wise on the GraphLab Server side, and is stored on persistent storage (e. Default behavior is to infer the column names: if no names are passed the behavior is identical to header=0 and column names are inferred from the first line of the file, if column names are passed explicitly then the behavior is identical to header=None. The first argument to reader() is. Transpose a. This will split the the STRING at every match of. Double quotes are used to wrap values that contain special characters such as commas, double quotes, new lines, etc. Each value is a field (or column in a spreadsheet), and each line is a record (or row in a spreadsheet). frequency 1,10 2,30 3,20 4,70. 7 support as well. split() has changed between Python versions when the regular expression can find zero-length matches. Ask Question Asked 7 years, 7 months ago. Python | Pandas Split strings into two List/Columns using str. So, reformatting the earlier data example as CSV would look like this:. The CSV format is one of the most flexible and easiest format to read. Active 7 years, 7 months ago. Python CSV Files: Reading and Writing - DZone Big Data / Big. While it would be pretty straightforward to load the data from these CSV files into a database, there might be times when you don’t have access to a database server and/or you don’t want to go through the hassle of setting up a server. Use index_label=False for easier importing in R. The data will be loaded using Python Pandas, a data analysis module. Open source software is made better when users can easily contribute code and documentation to fix bugs and add features. Copy the CSV file (so you have two identical files). 1GHz Athlon and Python 2. Add and Populate Column in CSV File Welcome › Forums › General PowerShell Q&A › Add and Populate Column in CSV File This topic contains 4 replies, has 5 voices, and was last updated by. I tried it using Python and completed the task. split column in pandas|pandas split one column into multiple columns|python pandas pandas rename column | How to rename column name in pandas | python pandas Skip navigation Sign in. The file has many columns for real estate sales such as date, location and price. csv") define the data you want to add color=['red' , 'blue' , 'green. This module is similar to the csv. How do I do this in Python? CSV File structured as follows:. The columns are frame, x, y, z variations written by another script from motion tacking data. This tutorial explains various methods to import data in Python. The second—and the main—thing you should see is that the bare. The ability to write short programs that are just as powerful as a program written in another language designed to do the same thing. Stack Exchange Network. Default behavior is to infer the column names: if no names are passed the behavior is identical to header=0 and column names are inferred from the first line of the file, if column names are passed explicitly then the behavior is identical to header=None. This is the opposite of concatenation which merges or combines strings into one. As long as the. In this lesson, you will learn how to access rows, columns, cells, and subsets of rows and columns from a pandas dataframe. py helps analyze new PYTHONDUMPREFS output. read_csv('survey_results_public. pyx script which provides the function must have have static C data types in order for the main Python script to gain full speed performance. How to read and write a CSV files. These two excel files should contain data from input. You can add custom text around the field value by using the template feature. Please help. For present purposes, authors may assume that the data fields contain no commas, backslashes, or quotation marks. Securely split a CSV file - perfect for private data How to open a large CSV file How to reorder and/or remove columns in a CSV file How to detect and remove duplicate rows from a CSV file CSV Splitter How to split a csv file by rows How to Split a CSV in Python How to split a CSV file in Google Drive. Can anyone help me with a Shell Script that can split and create new CSV files based on the data in column?. The \t in the text above means tabs. INSERT INTO tab (`col1`, `col2`, `col3`) VALUES (1,2,1), (1,2,2), (1,2,3);. The only thing is that the populated cells in each row of the CSV file do not match the CSV's column headers (as you correctly indicated that this would happen in your earlier post). A CSV file may look a little messier when you open it in a text editor, but it can be helpful to always continue thinking of it as a grid structure. Background: I'm extracting values from a file which is sometimes an xls and sometimes an xlsx file. If you'd prefer a video format for learning to program, you can use the discount code LOWESTPRICE to get an 80% discount. The script below does just that however, the columns data is from one row. Intuitively we'd expect to find some correlation between price and. Generating SQL inserts from csv data. How do I split a column of a csv file in excel using python 3. "Comma"-Separated Values Files $ python >>> capitals = {} # initialize a dictionary to hold our capitals data Column Headers in CSV Files. To get started, click the browse button to the right of the “Filename” field, and select the CSV or TXT file you want to split into multiple smaller ones. All file methods that we have mentioned - read , readline , and readlines , and simply iterating over the file object itself - will work on CSV files. disk) to avoid being constrained by memory size. ) The Python2 csv module takes 2x longer than a naive split(‘,’). Next I tried a run of each method using 500,000 integers concatenated into a string 2,821 kB long. Comma-separated value data is likely the structured data format that we’re all most familiar with, due to CSV being easily-consumed by spreadsheet applications. Here is the section on Python's csv module with a few examples from the official docs. In our previous data representations course, we learned how to read data from files and to work with strings. Delimitator - Specifies the delimitator in the CSV file. Numpy_Example_List_With_Doc has these examples interleaved with the built-in documentation, but is not as regularly updated as this page. If you know that your actual case IS the CSV file with a single column, and you will want to add more columns later, you can still use the csv. head() col1 col2 0 Arizona 373 1 California 371 2 Colorado 453 >. 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: