Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Server Side Programming Articles
Page 1088 of 2109
Node.js – util.inherits() Method
The util.inherits() method basically inherits the methods from one construct to another. This prototype will be set to a new object to that from the superConstructor.By doing this, we can mainly add some validations to the top of Object.setPrototypeOf(constructor.prototype, superConstructor.prototype).Syntaxutil.inherits(constructor, superConstructor)ParametersThe parameters are described below -constructor − This is a function type input that holds the prototype for constructor the user wants to be inherited.superConstructor − This is the function that will be used for adding and validating the input validations.Example 1Create a file "inherits.js" and copy the following code snippet. After creating the file, use the command "node inherits.js" to run ...
Read MoreNode.js – forEach() Method
The forEach() method in Node.js is used for iterating over a set of given array items. One can iterate over all the values of the array one-by-one using the forEach array loop.SyntaxarrayName.forEach(function)Parametersfunction − The function takes input for the method that will be executed.arrayName − Array that will be iterated.Example 1Create a file "forEach.js" and copy the following code snippet. After creating the file, use the command "node forEach.js" to run this code.// forEach() Demo Example // Defining a vehicle array const vehicleArray = ['bike', 'car', 'bus']; // Iterating over the array and printing vehicleArray.forEach(element => { console.log(element); });OutputC:\homeode>> ...
Read MoreDetermining the User IP Address in Node
Node.js is a completely open source technology that runs on JavaScript runtime environment. When the users want to access a website or link, they connect with the link using their system IP. We can use the dns.lookup() method in Node to find the IP address of the current user.Syntaxdns.lookup(hostname, [options], callback)ParametersThe parameters are described below −hostname − This input parameter consists of the web link which is valid or active.options − Default is 0. It takes input for the IP type, i.e., 4 for Ipv4 and 6 for Ipv6.callback − Handles any error if it occursExample 1Create a file with ...
Read MoreNode.js – hash.digest() Method
The Hash class is one of the many utility classes that is used for creating the hash digests of data. The hash.digest() method calculates all the data that needs to be hashed passed inside the hash function and returns them. If an encoding is defined, a string will be returned, else a buffer is returned.Syntaxhash.digest([encoding])ParametersIt takes a single parameter −encoding − This input parameter takes input for the encoding to be applied while calculating the hash.Example 1Create a file with the name "hashDigest.js" and copy the following code snippet. After creating the file, use the command "node hashDigest.js" to run ...
Read MoreNode.js – util.debuglog() Method
The util.debuglog() method creates a function that can be used to write the desired error/debug messages to stderr. These error messages are written only upon the existence of the NODE_DEBUG environment variable.Syntaxutil.debuglog(section, [callback])ParametersThe parameters are described below −section − This parameter takes the portion of the application for which the debug log is being created.callback − This is the callback function which will receive the pointer if any error occurs during the execution of method.Example 1Create a file with the name "debuglog.js" and copy the following code snippet -// util.debuglog() demo example // Importing the util module const util ...
Read MoreHow to iterate over rows in a DataFrame in Pandas?
To iterate rows in a DataFrame in Pandas, we can use the iterrows() method, which will iterate over DataFrame rows as (index, Series) pairs.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Iterate df using df.iterrows() method.Print each row with index.Exampleimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 1, 9], "y": [4, 1, 5, 10], "z": [4, 1, 5, 0] } ) print "Given DataFrame:", df for index, row in df.iterrows(): print "Row ", index, "contains: " print row["x"], row["y"], row["z"]OutputGiven DataFrame: x y z 0 5 4 4 1 2 1 1 2 1 5 5 3 9 10 0 Row 0 contains: 5 4 4 Row 1 contains: 2 1 1 Row 2 contains: 1 5 5 Row 3 contains: 9 10 0
Read MoreSelect rows from a Pandas DataFrame based on column values
To select rows from a DataFrame based on column values, we can take the following Steps −Create a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame.Use df.loc[df["x"]==2] to print the DataFrame when x==2.Similarly, print the DataFrame when (x >= 2) and (x < 2).Exampleimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 1, 9], "y": [4, 1, 5, 10], "z": [4, 1, 5, 0] } ) print "Given DataFrame is:", df print "When column x value == 2:", df.loc[df["x"] == 2] ...
Read MoreHow to rename column names in a Pandas DataFrame?
To rename columns in a Pandas DataFrame, we can override df.columns with the new column names.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame.Override the columns with new list of column names.Print the DataFrame again with the renamed column names.Exampleimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 1, 9], "y": [4, 1, 5, 10], "z": [4, 1, 5, 0] } ) print("Input DataFrame is:", df) df.columns = ["a", "b", "c"] print("After renaming, DataFrame is:", df)OutputInput DataFrame is: x y z 0 5 4 4 1 2 1 1 2 1 5 5 3 9 10 0 After renaming, DataFrame is: a b c 0 5 4 4 1 2 1 1 2 1 5 5 3 9 10 0
Read MoreSelect multiple columns in a Pandas DataFrame
To select multiple columns in a Pandas DataFrame, we can create new a DataFrame from the existing DataFrameStepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame.Create a new DataFrame, df1, with selection of multiple columns.Print the new DataFrame with multiple selected columns.Exampleimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 1, 9], "y": [4, 1, 5, 10], "z": [4, 1, 5, 0] } ) print "Input DataFrame is:", df df1 = df[['x', 'y']] print "After selecting multiple columns:", df1OutputInput DataFrame is: x y z 0 5 4 4 1 2 1 1 2 1 5 5 3 9 10 0 After selecting multiple columns: x y 0 5 4 1 2 1 2 1 5 3 9 10
Read MoreHow to get the row count of a Pandas DataFrame?
To get the row count of a Pandas DataFrame, we can use the length of DataFrame index.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame.Print the length of the DataFrame index list, len(df.index).Exampleimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 1, 9], "y": [4, 1, 5, 10], "z": [4, 1, 5, 0] } ) print "Input DataFrame is:", df print "Row count of DataFrame is: ", len(df.index)OutputInput DataFrame is: x y z 0 5 4 4 1 2 1 1 2 1 5 5 3 9 10 0 Row count of DataFrame is: 4
Read More