Tutorial by Examples: g

There are various methods available for explicitly converting a string to an integer, such as: Convert.ToInt16(); Convert.ToInt32(); Convert.ToInt64(); int.Parse(); But all these methods will throw a FormatException, if the input string contains non-numeric characters. For t...

Floating-point numbers cannot represent all real numbers. This is known as floating point inaccuracy. There are infinitely many floating points numbers and they can be infinitely long (e.g. π), thus being able to represent them perfectly would require infinitely amount of memory. Seeing this was a ...

Objective-C NSString *textToShare = @"StackOverflow Documentation!! Together, we can do for Documentation what we did for Q&A."; NSURL *documentationURL = [NSURL URLWithString:@"http://stackoverflow.com/tour/documentation"]; NSArray *objectsToShare = @[textToShare, docum...

Steps to create Hello Spring: Investigate Spring Boot to see if that would better suit your needs. Have a project set up with the correct dependencies. It is recommended that you are using Maven or Gradle. create a POJO class, e.g. Employee.java create a XML file where you can define your clas...

You can remove any of the conventions defined in the System.Data.Entity.ModelConfiguration.Conventions namespace, by overriding OnModelCreating method. The following example removes PluralizingTableNameConvention. public class EshopContext : DbContext { public DbSet<Product> Products...

string str = "this--is--a--complete--sentence"; string[] tokens = str.Split(new[] { "--" }, StringSplitOptions.None); Result: [ "this", "is", "a", "complete", "sentence" ]

for comprehensions in Scala are just syntactic sugar. These comprehensions are implemented using the withFilter, foreach, flatMap and map methods of their subject types. For this reason, only types that have these methods defined can be utilized in a for comprehension. A for comprehension of the fo...

It is also possible to use Scala's string interpolation feature to create elaborate extractors (pattern matchers), as perhaps most famously employed in the quasiquotes API of Scala macros. Given that n"p0${i0}p1" desugars to new StringContext("p0", "p1").n(i0), it is p...

To the average R user, the list structure may appear to be the one of the more complicated data structures to manipulate. There are no guarantees that all the elements within it are of the same type; There is no guaranteed structure of how complicated/non-complicated that the list would be (An eleme...

rvest is a package for web scraping and parsing by Hadley Wickham inspired by Python's Beautiful Soup. It leverages Hadley's xml2 package's libxml2 bindings for HTML parsing. As part of the tidyverse, rvest is piped. It uses xml2::read_html to scrape the HTML of a webpage, which can then be sub...

The r method implicitly provided via scala.collection.immutable.StringOps produces an instance of scala.util.matching.Regex from the subject string. Scala's triple-quoted string syntax is useful here, as you do not have to escape backslashes as you would in Java: val r0: Regex = """(...

Comparing string in a case insensitive way seems like something that's trivial, but it's not. This section only considers unicode strings (the default in Python 3). Note that Python 2 may have subtle weaknesses relative to Python 3 - the later's unicode handling is much more complete. The first thi...

Logistic regression is a particular case of the generalized linear model, used to model dichotomous outcomes (probit and complementary log-log models are closely related). The name comes from the link function used, the logit or log-odds function. The inverse function of the logit is called the lo...

When an exception is thrown from within a Future, you can (should) use recover to handle it. For instance, def runFuture: Future = Future { throw new FairlyStupidException } val itWillBeAwesome: Future = runFuture ...will throw an Exception from within the Future. But seeing as we can predic...

Using @import allows you to split up your files into multiple smaller files. This makes sense, as you are able to keep better structure for your stylesheets and avoid very large files. Example Let's say you have a few files. - application.scss - header.scss - content |-- article.scss '-- ...

.message color: white background: black .message-important @extend .message font-weight: bold .message-error @extend .message-important font-style: italic This code causes .message-error to extend from .message-important, which means that it will contain code from both .me...

If the file does not contain a header row, File: 1;str_data;12;1.4 3;str_data;22;42.33 4;str_data;2;3.44 2;str_data;43;43.34 7; str_data; 25; 23.32 you can use the keyword names to provide column names: df = pandas.read_csv('data_file.csv', sep=';', index_col=0, ski...

generate sample data frames: In [57]: df3 = pd.DataFrame({'col1':[211,212,213], 'col2': [221,222,223]}) In [58]: df1 = pd.DataFrame({'col1':[11,12,13], 'col2': [21,22,23]}) In [59]: df2 = pd.DataFrame({'col1':[111,112,113], 'col2': [121,122,123]}) In [60]: df3 = pd.DataFrame({'col1':[211,2...

import string import numpy as np import pandas as pd generate sample DF with various dtypes df = pd.DataFrame({ 'int32': np.random.randint(0, 10**6, 10), 'int64': np.random.randint(10**7, 10**9, 10).astype(np.int64)*10, 'float': np.random.rand(10), 'string': ...

import os, time import pyodbc import pandas.io.sql as pdsql def todf(dsn='yourdsn', uid=None, pwd=None, query=None, params=None): ''' if `query` is not an actual query but rather a path to a text file containing a query, read it in instead ''' if query.endswith('.sql') and o...