Anaconda Nltk Stopwords Download

They are extracted from open source Python projects. Summary – Anaconda vs Python Programming. import nltk nltk. Please try again later. Stopwords filter for 42 languages. Wolf has been splitted and now we have “clean” words to match against stopwords list. Natural Language Processing, AKA Computational Linguistics enable computers to derive meaning from human or natural language input. ini sudah tidak perlu di siapkan. OR, you can download the file nltk_data. Note that this will take a long time if your. If you are not using an Anaconda installation of Python then you can install with pip: pip install gensim. download('stopwords'). In this Python Anaconda tutorial, you will learn about Anaconda and its benefits, the installation process and how you can work with Anaconda, and in the end, we will peek over the companies that are using Anaconda in their workflow. It's done so because those words can have some sentiment impact in our review dataset. import nltk. Welcome - [Instructor] So let's jump in where we left off previously. This article discusses the Python programming language and its NLTK library, then applies them to a machine learning project. NLTK module has many datasets available that you need to download to use. Step2 : 문장을 입력 받아. feature_extraction import text stop = text. Anaconda Community Open Source NumFOCUS Support. Let's start coding: import nltk nltk. NLTK provides support for a wide variety of text processing tasks. It can tell you whether it thinks the text you enter below expresses positive sentiment, negative sentiment, or if it's neutral. Install PyPDF2, textract and nltk Python Modules. The removal of stop words may or may not increase the performance of your model. Explore NLP prosessing features, compute PMI, see how Python/Nltk can simplify your NLP related t…. 7 kB) File type Source Python version None Upload date Mar 25, 2017 Hashes View hashes. Stop words: Stop Words are words which do not contain important significance to be used in Search Queries. #Importing all the packages from lxml import html import json import string from dateutil import parser as dateparser from time import sleep from nltk. These are a form of "stop words," which we can also handle for. Removal Of Stop Words: It is common practice to remove words that appear frequently in the English language such as 'the', 'of' and 'a' (known as stopwords) because they're not so interesting. To get English stop words, you can use this code:. python nltk stopwords download (5) ipython 노트북 (또는 사용중인 다른 텍스트 편집기 / IDE)에서이 명령을 실행하기 만하면됩니다. We can import it by writing the following command on the Python command prompt − >>> import nltk Downloading NLTK’s Data. tokenize import word_tokenize # tokenize a document into words from nltk. This becomes handy. NLTK starts you off with a bunch of words that they consider to be stop words, you can access it via the NLTK corpus with: from nltk. To give a small synopsis, a stopword is a word that, though it has significant syntactic value in sentence formation, carries very negligible. They are extracted from open source Python projects. anaconda安装NLTK详细说明: 1. import pandas as pd import numpy as np import gzip import re from nltk. tokenize import sent_tokenize from nltk. conda install -c anaconda nltk Description NLTK has been called a wonderful tool for teaching and working in computational linguistics using Python and an amazing library to play with natural language. Go ahead and just download everything - it will take awhile but then you'll have what you need moving forward. Now it works!! I have installed NLTK and tried to download NLTK Data. 8 as of Oct 2014. This video will describe what software we will need to get started with the course and will demonstrate how to download, install, and set up the NLTK library. Last time we learned how to use stopwords with NLTK, today we are going to take a look at counting frequencies with NLTK. stem import PorterStemmer. 4; To install this package with conda run one of the following: conda install -c conda-forge nltk. To use the NLTK for pos tagging you have to first download the averaged perceptron tagger using nltk. I tried installing it from below command, but It installs all the packages that I do not need. Now after importing NLTK, we need to download the required data. They can safely be ignored without sacrificing the meaning of the sentence. Recipe: Text classification using NLTK and scikit-learn. Step 2) Enter the commands; import nltk nltk. If your web connection uses a proxy server, you should specify the proxy address as follows. 打开anaconda中的spyder2. Word Mover’s Distance (WMD) is a promising new tool in machine learning that allows us to submit a query and return the most relevant documents. Some tools avoid removing stop words to support phrase search. Stopwords are the frequently occurring words in a text document. Some of them are Punkt Tokenizer Models, Web Text Corpus, WordNet, SentiWordNet. load("en") text = """Most of the outlay will be at home. download(“averaged_perceptron_tagger”). Note that these are the pre-processed documents, meaning stopwords are removed, punctuation is removed, etc. txt','r',errors = 'ignore') raw=f. Maybe we're trying to classify it by the gender of the author who wrote it. Home Courses AD-Click Predicition Python, Anaconda and relevant packages installations Python, Anaconda and relevant packages installations Instructor: Applied AI Course Duration: 23 mins Full Screen. feature_extraction import text stop = text. However, we do have. You can specify the backoff sequence using the --sequential argument, which accepts any combination of the following letters:. NLTK Corpora Data. To use stopwords corpus, you have to download it first using the NLTK downloader. The difference between Anaconda and Python Programming is that Anaconda is a distribution of the Python and R programming languages for data science and machine learning while Python Programming is a high-level, general-purpose programming language. Download Anaconda; Sign In; conda-forge / packages / nltk_data 2019. You can vote up the examples you like or vote down the ones you don't like. download(‘popular’). The following are code examples for showing how to use nltk. Some of them are Punkt Tokenizer Models, Web Text Corpus, WordNet, SentiWordNet. Stop words and The Who (Wikipedia) Arpabet and CMU Pronouncing Dictionary (Wikipedia) Field Linguist's Toolbox (SIL International) About WordNet by George Miller et al. All the steps below are done by me with a lot of help from this two posts. import nltk nltk. In this tutorial know how to create a wordcloud from a corpus using nltk python module. These packages may be installed with the command conda install PACKAGENAME and are located in the package repository. 5 source activate mapr_nltk Note that some builds of PySpark are not compatible with Python 3. Import libraries import pandas as pd import gensim import nltk from nltk. In this step, I will use the Python standard os module and NLTK Library. With most of this processing, we're going to utilize the NLTK package for Python. Installing NLTK library. For example, from nltk. GitHub Gist: instantly share code, notes, and snippets. I uninstalled 3. でインストールできます。 ストップワードは、 import nltk from nltk. Before we can proceed with the code, we need to download the following libraries: Chatbot development falls in the broader category of Natural Language processing. Natural Language Processing, AKA Computational Linguistics enable computers to derive meaning from human or natural language input. 打开anaconda中的spyder 2. RegexpParser(). tokenize import RegexpTokenizer from nltk. Exploring the NLTK Book Corpus with Python. Research. To download NLTK Data, execute the following commands in Anaconda Prompt. We can import it by writing the following command on the Python command prompt − >>> import nltk Downloading NLTK's Data. In this section, we'll do tokenization and tagging. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. # File name: NLTK_presentation_code. msi and Copy and Paste nltk_data from H:\ nltk_data to C:\ nltk_data, or download nltk_data. Note that this will take a long time if your. Some of the Stopwords in English language can be - is, are, a, the, an etc. Regular expressions are a way to parse text using symbols to represent different kinds of textual characters. 2; Filename, size File type Python version Upload date Hashes; Filename, size many-stop-words-. Filter stop words from the words variable. If you are using Anaconda, most probably nltk would be already downloaded in the root (though you may still need to download various packages manually). download()3. ini sudah tidak perlu di siapkan. J'ai fait quelques recherches et j'ai trouvé que nltk ont des mots d'arrêt mais quand j'exécute la commande il y a une erreur. When I run this code via UiPath, I am getting the same value as what I am passi…. download () This should bring up a window showing available models to download. I can install with pip3 install, but I need to install with conda install so I can use the package. We also download the English nltk stopwords. Then you will apply the nltk. Python NLP tutorial: Using NLTK for natural language processing Posted by Hyperion Development In the broad field of artificial intelligence, the ability to parse and understand natural language is an important goal with many applications. msi and Copy and Paste nltk_data from H:\ nltk_data to C:\ nltk_data, or download nltk_data. import nltk nltk. corpus import stopwords. Hello and welcome to the 3rd part of this series on Twitter Sentiment Analysis using NLTK. 0), note that some of the APIs have changed in Version 3 and are not backwards compatible. Otherwise you may get following error: except LookupError: raise e LookupError:. tokenize import sent_tokenize from nltk. Okay, let’s start with the code. The chatbot uses the Natural Language Processing Toolkit (NLTK) to process the textual information. Let’s load the stop words of the English language in python. Natural language Processing With SpaCy and Python In this lesson ,we will be looking at SpaCy an industrial length Natural language processing library. So installieren Sie NLTK mit Continuum's anaconda / conda. In the script above, we first import the wikipedia and nltk libraries. There are more features of Anaconda cloud that we have not explored. To install NLTK with Continuum's anaconda / conda. pip install nltk; to download only tools/data used in this lesson: python -m nltk. In this tutorial I will teach you the steps for Installing NLTK on Windows 10. They are extracted from open source Python projects. import nltk. Topic modeling is an interesting task for someone to start getting familiar with NLP. Sentiment Analysis with Python NLTK Text Classification. Creating Custom Corpora 46 Setting up a custom corpus A corpus is a collection of text documents, and corpora is the plural of corpus. download ('stopwords') from nltk. The final few weeks of the program were dedicated to individual capstone projects of our choosing. Part of Speech Tagging with Stop words using NLTK in python The Natural Language Toolkit (NLTK) is a platform used for building programs for text analysis. import nltk nltk. download() First step is to install the stopwords so we run…. The Function nltk. Updates: 03/22/2016: Upgraded to Python version 3. NLTK stands for "Natural Language Tool Kit". A stopword is a frequent word in a language, adding no significative information ("the" in English is the prime example. Third source can be translation of English Stop words available in NLTK corpus into Hindi using translator. Download the Developer Editon for Crystal Reports for Visual Studio & Crystal Reports Runtime for both 64 and 32bit editions of the Visual Studio. Download it once and read it on your Kindle device, PC, phones or tablets. download(‘popular’). This package will help a lot in terms of cleaning your text data. conda install -c anaconda nltk Description NLTK has been called a wonderful tool for teaching and working in computational linguistics using Python and an amazing library to play with natural language. Let us begin! First of all, we will start by importing NLTK and String libraries and downloading some data needed to process text from nltk. The package nltk has a list of stopwords in English which you'll now store as sw and of which you'll print the first several elements. We can use that to filter out stop words from out sentence. After this runs my number of strings will drop to 40,631. tokenize import word_tokenize from nltk. 8 as of Oct 2014. Please help!. Related course: Easy Natural Language Processing (NLP) in Python. NLTK comes equipped with several stopword lists. This video tutorial shows you one way to install the NLTK Natural Language Toolkit Python module for Natural language processing through pip with Jupyter Notebook, an IDE in Anaconda Navigator. Python NLTK Exercises with Solution: The Natural Language Toolkit (NLTK) is a platform used for building Python programs that work with human language. Text summarization with NLTK The target of the automatic text summarization is to reduce a textual document to a summary that retains the pivotal points of the original document. download() in the IDLE prompt, and you get:. First, I load NLTK's list of English stop words. Download what you need. It's done so because those words can have some sentiment impact in our review dataset. Stopwords; from nltk. import nltk import string. With Anaconda Enterprise, you can do the following:. 6 and Anaconda. Let’s load the stop words of the English language in python. One of the more powerful aspects of the NLTK module is the Part of Speech tagging. The following are code examples for showing how to use nltk. We will talk about how to check model performance in the Model testing and evaluation section. download() After hitting this command the NLTK Downloaded Window Opens. HR1_token = nltk. >>> import nltk -- If you didn’t get nltk data downloaded last time, you can try again by typing >>> nltk. NLTK(Natural Language Toolkit) in python has a list of stopwords stored in 16 different languages. They are extracted from open source Python projects. Here is the list of NLTK stop words:. In this book, we will be using Python 3. It can be used to find the meaning of words, synonym or antonym. corpus import stopwords from nltk. How can I install stop-words for Anaconda, which I use for jupyter notebook with Anaconda-Navigator. You never know what you\'re gonna get. Dealing with text is hard! Thankfully, it’s hard for everyone, so tools exist to make it easier. Is anyone know how to install nltk on windows64 and python3. Then try from nltk. import nltk. Ainda não fiz nenhum post sobre text mining neste blog, o que é um pecado. Second is sarai. fileids(), you'll find out what. Natural Language Processing with NLTK. corpus import stopwords # 原始文本 raw_text = ' Life is like a box of chocolates. download (). Anaconda package lists¶. I used the NLTK interface. Installing NLTK library. 6) environment. ENGLISH_STOP_WORDS from sklearn. The object returned contains information about the downloaded page. download('popular') in Python work for you? alvations added windows related installation labels Mar 19, 2018 This comment has been minimized. Some of them are Punkt Tokenizer Models, Web Text Corpus, WordNet, SentiWordNet. NLTK is shipped with stop words lists for most languages. This package will help a lot in terms of cleaning your text data. Stack Exchange Network. download('stopwords') nltk. The major difference between these is, as you saw earlier, stemming can often create non-existent words, whereas lemmas are actual words. 6 de 64 bits. Please help!. You can use the stop word list returned by the stopWords function as a starting point. >>> import nltk -- If you didn’t get nltk data downloaded last time, you can try again by typing >>> nltk. corpus import stopwords. Such words are removed for NLP. Given a character sequence and a defined document unit, tokenization is the task of chopping it up into pieces, called tokens, perhaps at the same time throwing away certain characters, such as punctuation. Any set of words can be chosen as the stop words for a given purpose. Install Anaconda Distribution of Python and pip install NLTK. Skip to main content Switch to mobile version Download files. Это сработало для меня. 4; win-64 v3. Stop Words and Tokenization with NLTK: Natural Language Processing (NLP) is a sub-area of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (native) languages. download('inaugural') nltk. raw download clone embed report print Python 4. download() in the IDLE prompt, and you get:. If you have not previously loaded and saved the imdb data, run the following which will load the file from the internet and save it locally to the same location this is code is run from. In this tutorial. download("punkt") [nltk. Let’s start coding: import nltk nltk. Contribute to nltk/nltk_data development by creating an account on GitHub. It is imported with the following command: from nltk. download('punkt') nltk. J'ai fait quelques recherches et j'ai trouvé que nltk ont des mots d'arrêt mais quand j'exécute la commande il y a une erreur. spaCy 101: Everything you need to know The most important concepts, explained in simple terms Whether you're new to spaCy, or just want to brush up on some NLP basics and implementation details - this page should have you covered. The object returned contains information about the downloaded page. My idea: pick the text, find most common words and compare with stopwords. We can use that to filter out stop words from out sentence. Please help!. On this post, about how to use Stanford POS Tagger will be shared. Upon running the nltk. org on the whitelist (not sure if nltk is now downloaded more stuff than before). 現在4章まで実行中。課題はまだ残っています。順次作業中。 docker dockerを導入し、Windows, Macではdockerを起動しておいてください。 Windowsでは、BiosでIntel Virtualizationをenableにしないとdockerが起動しない場合があります。 また. Apri una console Python e fai quanto segue:. Estou usando o c9. Contribute to nltk/nltk_data development by creating an account on GitHub. We will load up 50,000 examples from the movie review database, imdb, and use the NLTK library for text pre-processing. I just realized that the nltk. Here is a sample of the command execution and results in Anaconda Prompt: $ python >>> import nltk >>> nltk. NLTK module has many datasets available that you need to download to use. words("english") Note that you will need to also do. NLTK, the Natural Language Toolkit, is a python package “for building Python programs to work with human language data”. raw download clone embed report print Python 4. # Import stopwords with scikit-learn from sklearn. Note that these are the pre-processed documents, meaning stopwords are removed, punctuation is removed, etc. 7 (Anaconda is a distribution of Python pre-packaged with many useful packages. 分析单词词性需要使用 python 的自然语言处理库 nltk 。 Anaconda 内置了 nltk 扩展包,需要小伙伴们打开 anaconda 的 promt ,输入以下命令安装 wordcloud 和结巴分词扩展库(安装链接见教程:作图详解|Anaconda扩展包的安装及bug处理): pip install wordcloud. 运行后会跳出一个nltk下载器窗口,点击下载即可. py If you need help installing TensorFlow, see our guide on installing and using a TensorFlow environment. download() command below, the the NLTK Downloader window will pop-up. Geocode the location to determine a latitude and longitude with the HERE Geocoder API. stem import WordNetLemmatizer from nltk. This dataset is available from NLTK. By default, NLTK contains some bunch of words that they consider to be stop words, you can access it via the NLTK corpus with: >>> import nltk >>> from nltk. You can easily download them from aptitude. In the context of nltk and python, it is simply the process of putting each token in a list. In this work, the Stop words list is the extended list using all three resources and contains words as well as phrases. corpus import stopwords. Download what you need. download()语句,下载相应的语料库和数据处理模型。 Python Module Index包含对模型的使用介绍。. One convient data set is a list of all english words, accessible like so. Extract locations from the text based on some clues with the Natural Language Toolkit (NLTK). Natural Language Processing: Python and NLTK - Kindle edition by Nitin Hardeniya, Jacob Perkins, Deepti Chopra, Nisheeth Joshi, Iti Mathur. And we will apply LDA to convert set of research papers to a set of topics. I wanted to show in a simple example how easy it is to process some text and assign a value to it in Python. We will load data into a pandas DataFrame. NLTK has a lot of supplementary resources that are only downloaded as they are needed, so the first time you run a program using NLTK, you'll probably be prompted to issue the command nltk. Text preprocessing is a severely overlooked topic and a lot NLP applications fail badly due to use of wrong kind of text preprocessing. import nltk nltk. (Princeton) NLTK 2. Removing stop words (i. The Natural Language Toolkit (NLTK) is a Python package for natural language processing. Release v0. Check complete details at https://www. Hi, I am trying to pass Body of the email to Python code and retrieve the email, phone number and names as an output from the python code. corpus import stopwords from nltk. linear_model import LogisticRegression from. Stop Words and Tokenization with NLTK: Natural Language Processing (NLP) is a sub-area of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (native) languages. GitHub Gist: instantly share code, notes, and snippets. Stopwords filter for 42 languages. In this step, I will use the Python standard os module and NLTK Library. corpus import stopwords from nltk. Command line installation¶. Please help!. This package will help a lot in terms of cleaning your text data. They are extracted from open source Python projects. Anaconda Distribution¶ The Most Trusted Distribution for Data Science. There is no universal list of stop words in nlp research, however the nltk module contains a list of stop words. Pada tulisan ini saya akan menjelaskan tentang proses Stopword Removal tentu saja dengan menggunakan Python Sastrawi. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and. Download full text PDF Natural Language Processing with Python The word set used in the title of p i is denoted as t i (stop words are removed) We use NLTK 36! Removing stop words with NLTK in Python GeeksforGeeks. Some of the Stopwords in English language can be – is, are, a, the, an etc. For example, the words like the, he, have etc. "book" or "reuters"). Fortunately NLTK has a lot of tools to help you in this task. Get list of common stop words in various languages in Python. To install NLTK with Continuum's anaconda / conda. Package Name Access Summary Updated oauth2client: public: No Summary 2017-03-10: rsa: None: Pure-Python RSA implementation 2017-03-10: oauth2. Words like the, a, I, is etc. NLTK has a number of stopwords listed under the “nltk. """ ChatterBot utility functions """ def import_module(dotted_path): """ Imports the specified module based on the dot notated import path for the module. Recipe: Text classification using NLTK and scikit-learn. tokenize import sent_tokenize from nltk. Step 1)Run the Python interpreter in Windows or Linux. Wordnet is an NLTK corpus reader, a lexical database for English. NLTK sudah siap dengan stopwords indonesian ~/nltk_data/corpora/stopwords/indonesian Download ID-Stopwords sudo apt install git git. import nltk nltk. For example, from nltk. corpus import stopwords from. Sign up to +=1 for access to these, video downloads, and no ads. Your feedback is welcome, and you can submit your comments on the draft GitHub issue. import nltk nltk. download('stopwords'). On Medium, smart voices and original ideas take center stage - with no ads in sight. download()语句,下载相应的语料库和数据处理模型。 Python Module Index包含对模型的使用介绍。. ) have been removed from the standard stopwords available in NLTK. The Natural Language Toolkit (NLTK) is a Python package for natural language processing. We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. 29) © 2019 Anaconda, Inc. import pandas as pd import matplotlib. でインストールできます。 ストップワードは、 import nltk from nltk. Is anyone know how to install nltk on windows64 and python3. To remove a custom list of stop words, use the removeWords function. Gathering the data. Often when working with text documents it is useful to filter out words that occur frequently in all documents (e. Get the Anaconda Cheat Sheet and then download. Go ahead and just download everything - it will take awhile but then you'll have what you need moving forward. download() After hitting this command the NLTK Downloaded Window Opens. ENGLISH_STOP_WORDS from sklearn. Some words (e. Anaconda comes with nltk pre-installed. Filtering stopwords in a tokenized sentence. If you want to learn more about NLTK, the O'Reilly book for Python 2 is a good resource, available here. tag import pos_tag Information Extraction. Is there any way to add. Load the example data. 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: