Pandas Sum Two Columns Into One

purchase price). I think you want to take a look at the dissolve method, where you can group by a certain column, take the union of the geometries for each group, and do another aggregation method on the other columns. Stackoverflow. Ravel() turns a Pandas multi-index into a simpler array, which we can combine into sensible column names:. Versions 2. As usual, the aggregation can be a callable or a string alias. The output is a Series object, which is a one dimensional array: sy1617['School_Type'] To access multiple columns, specify a list of column names. The sum represents total salary for each year (which is the grouping column). read_csv('sp500_ohlc. here 3 columns after 'Column2 inclusive of Column2 as OP asked). we might want to sort by the values in column B: >>> [] df. concatenate function from the masked array module instead. It is a multi-step process to do this in Excel but is fairly simple in pandas. values) As per this example (which also includes the source code of the assign function), you can also include more than one column:. python,indexing,pandas. Pandas provides the pandas. join(x), axis=1). merge operates as an inner join, which can be changed using the how parameter. SQL SUM() with where. of columns after that column (e. I think you want to take a look at the dissolve method, where you can group by a certain column, take the union of the geometries for each group, and do another aggregation method on the other columns. If others is specified, this function concatenates the Series/Index and elements of others element-wise. import pandas # Our small data set d = {'one':[1,1],'two':[2,2]} i = ['a','b'] # Create dataframe df = pandas. This book should not be your first. We often need to combine these files into a single DataFrame to analyze the data. sum Out[41]: second one 0. 00 now i have to add this, manually i can do it by saying column a + column b etc. 1, Column 2. Selecting multiple columns from DataFrame with duplicate column labels failure. I am new to the pandas framework and i want to know how can i get the count of all ItemID's associated with all the users, for the above dataset. seed(1) n = 10. I have read all the data into the pandas database but I am unsure on how to perform calculations on each individual file in the database (column calculations based on date and timestamp) and sum up all the solutions based on timestamps into one big csv file. How to join or concatenate two strings with specified separator; how to concatenate or join the two string columns of dataframe in python. 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. 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. Join the two dataframes along columns. concatenate function from the masked array module instead. In this example, we extract a new taxes feature by running a custom function on the price data. Note that ordering column values with Dask isn’t that easy (after all, the data is read one chunk at a time), so we cannot use the sort_values() method like we did in the Pandas example. If you are unfamiliar with concepts like cross-validation, random forest, and gradient descent, you will likely not benefit from this book as much as one of the many high-quality texts specifically designed to introduce you to the topic. To access an individual column, use square brackets. python,indexing,pandas. This T-SQL script will demo how to combine multiple rows into one row by a same column value in SQL Server. Pandas has two ways to rename their Dataframe columns, first using the df. many-to-one joins: for example when joining an index (unique) to one or more columns in a different DataFrame. 'agent_code' must be 'A003',. There are multiple ways to split an object like − obj. Since Pandas doesn't have an internal parallelism feature yet, it makes doing apply functions with huge datasets a pain if the functions have expensive computation times. Merging Datasets with Common Columns in Google Refine It's an often encountered situation, but one that can be a pain to address - merging data from two sources around a common column. Calculating sum of multiple. It has not actually computed anything yet except for some intermediate data about the group key df['key1']. We can use DataFrame. we will be finding the mean of a group in pandas, sum of a group in pandas python and count of a group. 1, Column 1. We can create the pandas data frame from multiple lists. 2-D arrays are stacked as-is, just like with hstack. ) In step_1 , I merged the two tables ( article_read and blog_buy ) based on the user_id columns. Because pandas need to maintain the integrity of the entire DataFrame, there are a couple more steps. Pandas dataframe. unstack: inverse operation from stack: “pivot” a level of the (possibly hierarchical) row index to the column axis, producing a reshaped DataFrame with a new inner-most level of column labels. Quantity Sold and Price Per Unit) and add the results of each individual calculation together. provide quick and easy access to pandas data structures across a wide range of use cases. When I try to add the other one, there is new entry in the Column Labels box that says values (essentially, all my averages or sums get turned into individual columns. Pandas is one of those packages and makes importing and analyzing data much easier. vast majority of typical use cases in finance, statistics, social science, and many areas of engineering. If your data had only one column, ndim would return 1. Pandas’ merge function has numerous options to help us merge two data frames. 0 2017-1-3 NaN 5. csv with the one of the corresponding column specified by in update. Note that ordering column values with Dask isn't that easy (after all, the data is read one chunk at a time), so we cannot use the sort_values() method like we did in the Pandas example. So, we added the Sum of Quantity again as a Row Heading - the right-most column in the screenshot. Machine Learning. Columns for each value of iaMean should appear in the table. SQL provides the INSERT statement that allows you to insert one or more rows into a table. Let's see how to use it, Select a Column by Name in DataFrame using loc[]. Now i want to plot total_year on line graph in which X axis should contain year column and Y axis should contain both action and comedy columns. Pandas distribute values of list element of a column into n different columns Pandas: sum up multiple columns into one column without last column Pandas Dataframe: split column into multiple columns, right-align inconsistent cell entries. "This grouped variable is now a GroupBy object. The sum of two convex functions (for example, L 2 loss + L 1 regularization) is a convex function. While this fragment is trivial, in the actual data I had 1,000s of rows, and many columns, and I wished to be able to group by different columns and then perform the stats below for more than one taget column. 0 For sum all columns use: df['Fruit Total']= df. In this post, I am going to discuss the most frequently used pandas features. For instance data from hospital events often contain one row for for each of the diagnostic categories the patient has received. The table should show have two columns (numHosts and Totals) and five rows in total after dragging. What I want to do is bring all this together in one sheet Possible? View 7. Script How to combine multiple rows into one row by a same column value (SQL) This site uses cookies for analytics, personalized content and ads. Column And Row Sums In Pandas And Numpy. How split a column in python How to split the column Fecha in two columns,for example, get a dataframe as follows: Trying to bin one column and sum the other. # With unnest you can convert one column into multiple ones. As usual, the aggregation can be a callable or a string alias. I tried to look at pandas documentation but did not immediately find the answer. If a grouping column contains a null, that row becomes a group in the result. Now convert the date column into. Pandas distribute values of list element of a column into n different columns Pandas: sum up multiple columns into one column without last column Pandas Dataframe: split column into multiple columns, right-align inconsistent cell entries. Since Pandas doesn't have an internal parallelism feature yet, it makes doing apply functions with huge datasets a pain if the functions have expensive computation times. sum() Following the same logic, you can easily sum the values in the water_need column by typing: zoo. values) As per this example (which also includes the source code of the assign function), you can also include more than one column:. Let's see how to. Begin by separating sex into two different DataFrames for later use. Now, we want to add a total by month and grand total. apply ( lambda row : row. As you can see, applying a custom function on one or more columns is very easy in both cases, we were even able to reuse the same function, just wrapped up differently for pandas and Spark. The AVG() function returns the average value of a numeric column. We can get position of column using. I think you want to take a look at the dissolve method, where you can group by a certain column, take the union of the geometries for each group, and do another aggregation method on the other columns. For example, the row 12 sum is not calculated as the sum of rows 3 to 12. Rather, we have two observations per row, one for home and one for away. import pandas as pd import numpy as np. Pandas dataframe. Splitting one Row with Multiple Columns into Multiple Rows. For example, suppose that in a column that contains numbers, you want to sum only the values that are larger than 5. plot() directly on the output of methods on GroupBy objects, such as sum(), size(), etc. I'm quite proficient in Excel but am struggling here, would really appreciate any help I basically have 80 tabs with IP addresses in Column A and then information in Columns B, C and D related to this. asked 3 hours ago in Data Science by ashely (20. when I use this syntax it creates a series rather than adding a column to my new dataframe (sum). here 3 columns after 'Column2 inclusive of Column2 as OP asked). "This grouped variable is now a GroupBy object. The pandas package provides various methods for combining DataFrames including merge and concat. sum(axis=1). Chapter 1: Getting started with pandas 2. By default, merge performs inner join operation on a common variable/column to merge two data frames. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas distribute values of list element of a column into n different columns Pandas: sum up multiple columns into one column without last column Pandas Dataframe: split column into multiple columns, right-align inconsistent cell entries. merge allows two DataFrames to be joined on one or more keys. Here is a simple example using a single column. Deep models are never convex functions. If a grouping column contains more than one null, the nulls are put into a single group. Watch this video to learn how to merge two columns in Excel without losing any data. Series arithmetic is vectorised after first. I have a pandas dataframe where one of the columns is a set of labels that I would like to plot each of the other columns against in subplots. Plotting two of the variables against one of the others. To make this easy, the pandas read_excel method takes an argument called sheetname that tells pandas which sheet to read in the data from. we will be finding the mean of a group in pandas, sum of a group in pandas python and count of a group. Pandas is proving two methods to check NULLs - isnull() and notnull() These two returns TRUE and FALSE respectively if the value is NULL. Helpful Python Code Snippets for Data Exploration in Pandas cleaning, or analysis using Python, Pandas will quickly become one of your most frequently used and reliable tools. This makes it easy to get the data for the month under consideration. Click Next, and add workbook(s) you will sum values into the Workbook lis t by clicking Add button, then check the sheets you want to combine in the Worksheet list. To do this, you need to create a new value for every row with one of two possible values: "Mobile" or "Desktop. Pandas - KeyError: columns not in index [on hold] dataframe to csv put output into one cell. apply to apply a function to all columns axis=0 (the default) or axis=1 rows. It contains high-level data structures and manipulation tools designed to make data analysis fast and easy. cat: >>> [] df [’cat’] We can also select a subset of the rows using slicing. The pandas package provides various methods for combining DataFrames including merge and concat. Two-dimensional Arrays Daniel Shiffman. Resultant dataFrame would be [patient_id, urine output, haemoglobin, Blood pressure]. How do I split one row into multiple rows with Excel? Ask Question Asked 6 years, 2 months ago. I am using python 2. At least one of the columns in the DataFrame should contain geometric information. Endnotes In this article, I have introduced you to some of the most common operations on DataFrame in Apache Spark. Can You Merge Data From Many Tabs Into One Overall Tab? Oct 23, 2007. I may be running two ads on different channels that overlap with each other — also valid. Example: csvtool pastecol 2-3 1- input. Let's see how to. The dataset has elements of categorical data in the “doctor_name” column. Now convert the date column into. here 3 columns after 'Column2 inclusive of Column2 as OP asked). Include only float, int, boolean columns. When more than one column header is present we can stack the specific column header by specified the level. apply ( lambda row : row. Among its scientific computation libraries, I found Pandas to be the most useful for data science operations. In this tutorial lets see. How Do I Combine Multiple Columns Into One Column in Excel 2010 September 27, 2012 By Matt Microsoft Excel 2010 spreadsheets provide a great way for you to separate related data so that you can sort and edit some information without affecting other information. It is very simple to add totals in cells in Excel for each month. Pivot takes 3 arguements with the following names: index, columns, and values. How split a column in python How to split the column Fecha in two columns,for example, get a dataframe as follows: Trying to bin one column and sum the other. I have two columns in Excel that I want to compare and find the differences between them. A COLUMNS statement can describe more than one column, and one column of the report can be described with several different COLUMNS statements. That's basically the question "how many NAs are there in each column of my dataframe"? This post demonstrates some ways to answer this question. You must enter at least one Column variable. vast majority of typical use cases in finance, statistics, social science, and many areas of engineering. Here one of the columns is sample IDs with two-part strings separated by underscore "_". melt works by taking observations that are spread across columns (away_team, home_team), and melting them down into one column with multiple rows. List of two column names: eventcol = [bio, procedure_codes] A common recommendation on Stackoverflow is to use apply and join. merge(): it looks for one or more matching column names between the two inputs, and uses this as the key. To do this, you need to create a new value for every row with one of two possible values: "Mobile" or "Desktop. Adding values in two columns to new column on sync table in CARTO? Don't use sum. Describe DataFrame columns >>> df. The values of the columns are averaged. 6 was the ability to pivot data, creating pivot tables, with a DataFrame (with Scala, Java, or Python). Is there a way to skip NaNs without. pandas: create new column from sum of others so we would have to assign the result into our new column. Lots of examples of ways to use one of the most versatile data structures in the whole Python data analysis stack. Pandas Create Structures s = Series (data, index) df = DataFrame (data, index, columns) p = Panel (data, items, major_axis, minor_axis) Create a Series. 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 hierarchical index. it can hadle string, # ### Create a Pandas UDF function that sum a values(32 in this case) to two. values) As per this example (which also includes the source code of the assign function), you can also include more than one column:. method to find the cumulative correlation between two pandas. (Which means that the output format is slightly different. The pivot function is used to create a new derived table out of a given one. This article will walk through the basic flow required to parse multiple Excel files, combine the data, clean it up and analyze it. B Column(s): One or more variables to use in the columns of the crosstab(s). These were implemented in a single python file. Pandas object can be split into any of their objects. split() Pandas provide a method to split string around a passed separator/delimiter. We will examine each function of the INSERT statement in the following sections. There are two types of advanced indexing: integer and Boolean. This also selects only one column, but it turns our pandas dataframe object into a pandas series object. It also takes three lines. You must enter at least one Column variable. inconveniently divided into 5 columns, however pandas’ concat method should help us concatenate them into one:. For example, you may have a data frame with data for each year as columns and you might want to get a new column which summarizes multiple columns. sum() function return the sum of the values for the requested axis. This makes interactive work intuitive, as there’s little new to learn if you already know how to deal with Python dictionaries and NumPy arrays. Note that ordering column values with Dask isn't that easy (after all, the data is read one chunk at a time), so we cannot use the sort_values() method like we did in the Pandas example. You want to make sure that the column and row structures match and that the values are in the same units, etc. groupby('key') obj. Notably, Pandas DataFrames are essentially made up of one or more Pandas Series objects. plot() directly on the output of methods on GroupBy objects, such as sum(), size(), etc. Pandas is one of those packages and makes importing and analyzing data much easier. numeric_only: bool, default None. (Which means that the output format is slightly different. All the data in a Series is of the same data type. We can easily create new columns, and base them on data in the other columns. With about 850 000 rows and two columns: %timeit df[eventcol]. 2 and Column 1. many-to-many joins: joining columns on columns. A mapping could be one of many things: A Python function, to be called on each label. Combining this in a single row with all migh be useful for several reasons. csv > output. This article focuses on providing 12 ways for data manipulation in Python. getting mean score of a group using groupby function in python. We load data into a DataFrame and create a GroupBy object using the groupingBy() method. i'm not sure if I understand what you mean ;) but you could combine two columns with string data into index like that: Recommend: python - Merge pandas dataframe, with column operation what key words to use) Here is my problem: I have a bunch of dataframes need to be merged; I also want to update the values of a subset of columns with the sum. As far as grouping, in a totally abstract sense we have to define some kind of mapping that assigns labels (one of the axes) into group buckets. It has not actually computed anything yet except for some intermediate data about the group key df['key1']. To do this in pandas, meet one of its workhorses, and also one of the reasons why the library has become so popular: the groupby operator. join or concatenate string in pandas python – Join() function is used to join or concatenate two or more strings in pandas python with the specified separator. copy and paste this URL into your. I was hoping for a way to combine a few of the tables into one big table. int_column == column of integers dec_column1 == column of decimals dec_column2 == column of decimals I would like to be able to groupby the first three columns, and sum the last 3. , a whole dataframe. Calculating sum of multiple. 'agent_code' must be 'A003',. If a grouping column contains a null, that row becomes a group in the result. Most of the time that’s through stackoverflow but here’s one that deals with parallelization and efficiency that I thought would be helpful. How to make multiple filters; read_csv errors of encoding; Dataframe functions. Here is an example of Left & right merging on multiple columns: You now have, in addition to the revenue and managers DataFrames from prior exercises, a DataFrame sales that summarizes units sold from specific branches (identified by city and state but not branch_id). Manipulating dataframes in python. Transpose/Convert columns and rows into single column with formula Tabbed browsing & editing multiple Excel workbooks/Word documents as Firefox, Chrome, Internet Explore 10! You may be familiar to view multiple webpages in Firefox/Chrome/IE, and switch between them by clicking corresponding tabs easily. The df contains the years that the team has existed. The simplest way to merge two data frames is to use merge function on first data frame and with the second data frame as argument. Suppose there is a dataframe, df, with 3 columns. A DataFrame in pandas is a 2-dimensional data structure which holds data in a tabular sense. csv > output. Pandas' drop function can be used to drop multiple columns as well. Indexing could mean selecting all the rows and some of the columns, some of the rows and all of the columns, or some of each of the rows and columns. While one simple way would be to copy and paste data from both worksheets into one and then create a pivot table, the following shortcomings exist with this method. Pandas: transforms lines into a single column based on state I have the following pandas dataframe named matches: id | name | age 1 | a | 19 1 | b | 25 2 | c | 19 2 | d | 22 I use a groupby + count(), if the value of a certain column (age) satisfies a condition (x < 21). ) In step_1 , I merged the two tables ( article_read and blog_buy ) based on the user_id columns. Here, each plot will be scaled independently. ) lives in two dimensions. sum() Following the same logic, you can easily sum the values in the water_need column by typing: zoo. So, basically Dataframe. About two years ago, I discovered pandas, a Python library for performing data analysis. Note that ordering column values with Dask isn't that easy (after all, the data is read one chunk at a time), so we cannot use the sort_values() method like we did in the Pandas example. Plotting two of the variables against one of the others. Stackoverflow. A Brief on DataFrames. Specify multiple grouping columns in the GROUP BY clause to nest groups. When I try to add the other one, there is new entry in the Column Labels box that says values (essentially, all my averages or sums get turned into individual columns. How To / Python: Combine multiple CSV files into one 3 Replies If you have multiple CSV files with the same structure, you can append or combine them using a short Python script. A COLUMNS statement can describe more than one column, and one column of the report can be described with several different COLUMNS statements. Indexing can also be known as Subset Selection. Descriptive statistics 3. 00 now i have to add this, manually i can do it by saying column a + column b etc. The agg method can take a list of functions as input. Scentellegher. Pandas DataFrame has sort_values() to correspond to the ORDER clause in SQL. I have a new column of data that I want to add to the csv file. This makes interactive work intuitive, as there’s little new to learn if you already know how to deal with Python dictionaries and NumPy arrays. To make this easy, the pandas read_excel method takes an argument called sheetname that tells pandas which sheet to read in the data from. You can first select by iloc and then sum: df['Fruit Total']= df. Compute the sum of Freq for each of them. Suppose you have a dataset containing credit card transactions, including: the date of the transaction; the credit card number; the type of the expense. Selecting multiple rows and columns in pandas. i can plot only 1 column at a time on Y axis using. Combining DataFrames with pandas. How to quickly merge rows based on one column value then do some calculations in Excel? For example, you have a range of data and one column has duplicates, now you want to merge rows bases the column A (has duplicates) then do some calculations to another column based on the merged rows as screenshot shown:. Copying and pasting data from multiple worksheets into one is a manual process; and 2. split() Pandas provide a method to split string around a passed separator/delimiter. Let us also create a new small pandas data frame with five columns to work with. We will examine each function of the INSERT statement in the following sections. Quantity Sold and Price Per Unit) and add the results of each individual calculation together. This article focuses on providing 12 ways for data manipulation in Python. With about 850 000 rows and two columns: %timeit df[eventcol]. I'd like to tack two new columns onto my frame, one for each part of the 2-tuple corresponding to the label for each row. ) Pandas Data Aggregation #2:. Chapter 1: Getting started with pandas 2. org to investigate the average life expectancy (in years) at birth in 2010 for the 6 continental regions. The Python and NumPy indexing operators [] and attribute operator. Series in Pandas – Series as an one-dimensional object that is similar to an array, list, or column in a database. Comedy Dataframe contains same two columns with different mean values. It also takes three lines. 1, Column 1. Create a Dataframe. For example, here is an apply() that normalizes the first column by the sum of the second:. Q&A for cartographers, geographers and GIS professionals. DataFrame or pandas. but i dont know how to compute via sum. Manipulating dataframes in python. These were implemented in a single python file. Series object: an ordered, one-dimensional array of data with an index. Account ID) and sum another column (e. You can do the whole filtering and sum using pandas' builtins: copy and paste this URL into your RSS reader. Seven Clean Steps To Reshape Your Data With Pandas Or How I Use Python Where Excel Fails 5" column contains two pieces of information. In Combine Worksheets step 1 dialog, check Consolidate and calculate values across multiple workbooks into one worksheet option. Finding the right vocabulary for. SQL provides the INSERT statement that allows you to insert one or more rows into a table. sort a dataframe in python pandas - By single & multiple column How to sort a dataframe in python pandas by ascending order and by descending order on multiple columns with an example for each. get_loc() - as answered here. As with many programming problems, there tends to be more than one solution. As a value for each of these parameters you need to specify. Now, DataFrames in Python are very similar: they come with the Pandas library, and they are defined as two-dimensional labeled data structures with columns of potentially different types. I tried doing this with pd. The specified column names must be valid SAS names. With about 850 000 rows and two columns: %timeit df[eventcol]. 240376 So the above uses rolling_sum and shift to. Percentile rank of a column in pandas python – (percentile value) Get the percentage of a column in pandas python; Cumulative percentage of a column in pandas python; Cumulative sum of a column in pandas python; Difference of two columns in pandas dataframe – python; Sum of two or more columns of pandas dataframe in python. It contains high-level data structures and manipulation tools designed to make data analysis fast and easy. Pandas dataframe. To insert one row into a table, you use the following syntax of the INSERT statement. convert keywords in one column into several dummy. that has multiple rows with the same name, title, and id, but different values for the 3 number columns (int_column, dec_column1, dec_column2). 6 was the ability to pivot data, creating pivot tables, with a DataFrame (with Scala, Java, or Python). Ravel() turns a Pandas multi-index into a simpler array, which we can combine into sensible column names:. which I am not covering here. Reshape array. cumsum¶ DataFrame. [code]>>> import pandas as pd >>> df = pd. Pandas DataFrame has sort_values() to correspond to the ORDER clause in SQL. Pandas, along with Scikit-learn provides almost the entire stack needed by a data scientist. , DataFrame, Series) or a scalar; the combine operation will be tailored to the type of output returned. 240376 So the above uses rolling_sum and shift to. See the Package overview for more detail about what’s in the library. at 1 row for example, i have data like 1. You can first select by iloc and then sum: df['Fruit Total']= df. Python Pandas : Select Rows in DataFrame by conditions on multiple columns Pandas : Get frequency of a value in dataframe column/index & find its positions in Python Pandas : 6 Different ways to iterate over rows in a Dataframe & Update while iterating row by row. 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. However, the power (and therefore complexity) of Pandas can often be quite overwhelming, given the myriad of functions, methods, and capabilities the library provides. 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. Create a Column Based on a Conditional in pandas. column_stack¶ numpy. Apr 23, 2014. Manipulating dataframes in python. cumsum (self, axis=None, skipna=True, *args, **kwargs) [source] ¶ Return cumulative sum over a DataFrame or Series axis. Multiply two columns and add up the results using SUMPRODUCT Tweet The SUMPRODUCT function allows you to multiply two columns or rows of numbers together (e. apply to apply a function to all columns axis=0 (the default) or axis=1 rows. In part 4 of the Pandas with Python 2. apply ( lambda row : row. The words "merge" and "join" are used relatively interchangeably in Pandas and other languages. Pandas has two ways to rename their Dataframe columns, first using the df. Pandas is arguably the most important Python package for data science. I feel like I am constantly looking it up, so now it is documented: If you want to do a row sum in pandas, given the dataframe df:. One cohort should be a data frame of right-handed batters. the number of columns in second dataFrame can vary because I am extracting them from the text. 1 are the methods append_to_multiple and select_as_multiple, that can perform appending/selecting from multiple tables at once. 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: