Tutorial by Examples: l

In [1]: import pandas as pd import numpy as np In [2]: df = pd.DataFrame(np.random.choice(['foo','bar','baz'], size=(100000,3))) df = df.apply(lambda col: col.astype('category')) In [3]: df.head() Out[3]: 0 1 2 0 bar foo baz 1 baz bar baz 2 foo foo b...

Detailed instructions on getting rdf set up or installed.

As the last layer created by docker build -t mytag . showed ---> Running in d9a42e53eb5a You just launch the last created image with a shell and launch the command, and you will have a more clear error message docker run -it d9a42e53eb5a /bin/bash (this assumes /bin/bash is available, it ma...

When displaying labels on contours Matlab doesn't allow you to control the format of the numbers, for example to change to scientific notation. The individual text objects are normal text objects but how you get them is undocumented. You access them from the TextPrims property of the contour handl...

This is a sample HTTP client based on Ev extension. Ev extension implements a simple yet powerful general purpose event loop. It doesn't provide network-specific watchers, but its I/O watcher can be used for asynchronous processing of sockets. The following code shows how HTTP requests can be sche...

Detailed instructions on getting javafx-8 set up or installed.

The ApplicationData.Current.LocalFolder api allows us to get access to the application cache : var file = await ApplicationData.Current.LocalFolder.CreateFileAsync("myFile.dat", CreationCollisionOption.ReplaceExisting); The FileIO class contains a set of utility methods to easily add d...

File descriptors and FILE objects are per-process resources that cannot themselves be exchanged between processes via ordinary I/O. Therefore, in order for two distinct processes to communicate via an anonymous pipe, one or both participating processes must inherit an open pipe end from the process...

Connecting two child processes via a pipe is performed by connecting each of two children to the parent via different ends of the same pipe. Usually, the parent will not be party to the conversation between the children, so it closes its copies of both pipe ends. int demo() { int pipefds[2]; ...

A shell-style pipeline consists of two or more processes, each one with its standard output connected to the standard input of the next. The output-to-input connections are built on pipes. To establish a pipeline-like set of processes, one creates pipe-connected child processes as described in ano...

Example of creating an empty HashTable: $hashTable = @{} Example of creating a HashTable with data: $hashTable = @{ Name1 = 'Value' Name2 = 'Value' Name3 = 'Value3' }

An example of defining a hash table and accessing a value by the key $hashTable = @{ Key1 = 'Value1' Key2 = 'Value2' } $hashTable.Key1 #output Value1 An example of accessing a key with invalid characters for a property name: $hashTable = @{ 'Key 1' = 'Value3' Key2 = 'Val...

$hashTable = @{ Key1 = 'Value1' Key2 = 'Value2' } foreach($key in $hashTable.Keys) { $value = $hashTable.$key Write-Output "$key : $value" } #Output Key1 : Value1 Key2 : Value2

An example, to add a "Key2" key with a value of "Value2" to the hash table, using the addition operator: $hashTable = @{ Key1 = 'Value1' } $hashTable += @{Key2 = 'Value2'} $hashTable #Output Name Value ---- -----...

The cluster library contains the ruspini data - a standard set of data for illustrating cluster analysis. library(cluster) ## to get the ruspini data plot(ruspini, asp=1, pch=20) ## take a look at the data hclust expects a distance matrix, not the original data. We ...

With hierarchical clustering, outliers often show up as one-point clusters. Generate three Gaussian distributions to illustrate the effect of outliers. set.seed(656) x = c(rnorm(150, 0, 1), rnorm(150,9,1), rnorm(150,4.5,1)) y = c(rnorm(150, 0, 1), rnorm(150,0,1), rnorm(150,5,1)) ...

This package is created to handle server-side works of DataTables jQuery Plugin via AJAX option by using Eloquent ORM, Fluent Query Builder or Collection. Read more about this here or here

Let df = pd.DataFrame({'col_1':['A','B','A','B','C'], 'col_2':[3,4,3,5,6]}) df # Output: # col_1 col_2 # 0 A 3 # 1 B 4 # 2 A 3 # 3 B 5 # 4 C 6 To get the distinct values in col_1 you can use Series.unique() df['col_1'].unique() # Output: ...

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Parallel extensions have been introduced along with the Task Parallel Library to achieve data Parallelism. Data parallelism refers to scenarios in which the same operation is performed concurrently (that is, in parallel) on elements in a source collection or array. The .NET provides new constructs t...