DEV Community: Punitha

Conditional Array Operations

Punitha — Thu, 03 Sep 2026 05:06:01 +0000

NumPy allows us to change values based on conditions. >, <, >=, and <=

Step 1:

Output:

Step 2: Greater than

Output:

Step 3: Less than

Output:

Step 4: Greater than or equal to

Output:

Step 5: Less than or equal to

Output:

Axis Operation

Punitha — Wed, 02 Sep 2026 13:39:35 +0000

Step 1:

Output:

Step 2: Axis = 0

Output:

Step 3: Axis = 1

Output:

Step 4: Axis = 0 (Max)

Output:

Step 5: Axis = 0 (argmax)

Output:

Statistical Operations

Punitha — Tue, 01 Sep 2026 16:59:22 +0000

NumPy can also perform common statistical calculations.

sum()

average()

mean()

std()

Sum

np.sum() calculates the total.

Output:

Average

np.average() calculates the average.

Output:

Mean

np.mean() calculates the arithmetic mean.

Output:

Standard Deviation

np.std() calculates the standard deviation.

Output:

Matrix Multiplication & Universal Functions

Punitha — Mon, 31 Aug 2026 04:48:02 +0000

What is Matrix Multiplication?

Matrix multiplication is an operation used to multiply two compatible arrays or matrices.

NumPy provides two common ways:

a @ b

and

np.matmul(a, b)

Step 1:

Output:

Universal Functions

Cumulative Sum – cumsum()

What is cumsum()?

cumsum() calculates the running total of the elements.

Step 1:

Output:

Cumulative Product – cumprod()

What is cumprod()?

cumprod() calculates the running multiplication of the elements.

Step 1:

Output:

Minimum and Maximum

NumPy provides functions to find the smallest and largest values.

min() & argmin()

min() returns the smallest value.

argmin() returns the index of the minimum value.

Step 1:

Output:

max() & argmax()

max() returns the largest value.

argmax() returns the index of the maximum value.

Step 1:

Output:

NumPy File I/O

Punitha — Wed, 26 Aug 2026 14:45:35 +0000

What is File I/O?

I/O means Input and Output.

Save arrays to files.

Load arrays from files.

Save Array as .npy

NumPy provides np.save() to save an array in NumPy's .npy format.

Step 1:

np.save("numpy.npy", a)

This saves the array as:

numpy.npy

Save Array as CSV

You can also save an array as a CSV file using np.savetxt().

Step 1:

np.savetxt("numpy.csv", a, delimiter=",")

"numpy.csv" → output file name

a → array to save

delimiter="," → values are separated by commas

Your file uses np.savetxt() with a comma delimiter.

Load Data from CSV

Use np.loadtxt() to read numerical data from a text/CSV file.

Step 1:

b = np.loadtxt("numpy.csv", delimiter=",")

Step 2:

Print the loaded data:

print(b)

Quick Reference

Function             Purpose

np.array()     -  Create an array
np.arange()    -  Create a sequence of numbers
reshape()      -  Change array shape
np.zeros()     -  Create an array filled with 0
np.ones()      -  Create an array filled with 1
np.empty()     -  Create an uninitialized array
np.full()      -  Create an array filled with a specified value
np.save()      -  Save an array as .npy
np.savetxt()       -  Save an array as text/CSV
np.loadtxt()       -  Load numerical data from text/CSV

Zeros, Ones, Empty and Default Value

Punitha — Tue, 25 Aug 2026 05:22:22 +0000

Create an Array of Zeros

What is np.zeros()?

np.zeros() creates an array where all elements are 0.

Step 1:

Output:

Create an Array of Ones

What is np.ones()?

np.ones() creates an array where all elements are 1.

Step 1:

Output:

Create an Empty Array

What is np.empty()?

np.empty() creates an array with a specified shape without initializing its values.

Step 1:

Output:

Create an Array with a Default Value

What is np.full()?

np.full() creates an array where every element has the same specified value.

Step 1:

Output:

Slicing, Creation, Reshape

Punitha — Mon, 24 Aug 2026 02:53:29 +0000

What is Array Slicing?

Slicing is used to extract a part of an array.

Step 1: Create 2D Array

Step 2: Slice Rows and Columns

Output:

Creating Arrays Using arange()

What is np.arange()?

np.arange() creates an array containing a sequence of numbers.

Output:

Why use arange()?

Quickly create number sequences.
Useful for testing.
Useful for creating arrays for calculations.

Reshape an Array

What is reshape()?

reshape() changes the shape of an array without changing the number of elements.

Step 1:

Step 2: Reshape

Output:

NumPy Array

Punitha — Fri, 21 Aug 2026 01:58:24 +0000

What is a NumPy Array?

A NumPy array is a collection of values stored in a structured way.

Numpy also supports:

1D arrays
2D arrays
3D arrays
Higher-dimensioanl arrays

Access Array Elements

We can access individual elements using their index.

arr = np.array([10, 20, 30, 40])

print(arr[0])
print(arr[3])

Output:

10
40

Array Slicing

Slicing is used to extract a portion of an array.

arr = np.array([10, 20, 30, 40])

print(arr[0:3])

Output:

[10 20 30]

1D Array

A 1D array contains values in a single row.

Output:

Attributes:

Output:

2D Array

A 2D array contains rows and columns.

Output:

Attributes:

Output:

3D Array

NumPy can also create 3D arrays.

Output:

Attributes:

Output:

Introduction of NumPy

Punitha — Thu, 20 Aug 2026 03:24:06 +0000

What is NumPy?

NumPy (Numerical Python) is a Python library used for numerical and scientific computing.
It provides a powerful data structure called an array, which is useful for storing and processing numerical data.

Why Use NumPy?

It works efficiently with numerical data.
It provides powerful array operations.
It supports multi-dimensional arrays.
It provides mathematical functions.
It is widely used in Data Science and Machine Learning.

Installing NumPy

Step 1:

Open Command Prompt or VS code Terminal

Step 2:

Run:

pip install numpy

Step 3:

Wait until the installation is completed.

Step 4: Import NumPy

After installation, import NumPy into your Python program.

import numpy as np

numpy is the library name.

np is the commonly used alias for NumPy.

Step 5: Check NumPy Version

print(np.__version__)

NumPy Array Attributes

NumPy provides useful attributes to understand an array.

Size - size tells the total number of elements.

ndim - ndim tells the numbers of dimensions.

dtype - dtype tells the data type of the elements.

itemsize - itemsize tells how many bytes are used by each element.

shape - shape tells the size of each dimension.

Calculated Fields in Tableau

Punitha — Wed, 19 Aug 2026 04:20:43 +0000

What is a Calculated Field?

A Calculated Field is a custom field created using formulas to perform calculations on existing data.

Why Use Calculated Fields?

Create new measures.
Perform calculations.
Create categories.
Calculate Profit Ratio.
Calculate Growth Percentage.

How to Create a Calculated Field

Step 1

Go to:

Analysis
        ↓
Create Calculated Field

Step 2

Enter a name.

Example:

Profit Ratio

Step 3

Write Formula:

SUM([Profit]) / SUM([Sales])

Click OK.

Example 1: Profit Ratio

Formula:

SUM([Profit]) / SUM([Sales])

Example 2: Discount Category

Formula:

IF [Discount] > 0.20 THEN
"High Discount"
ELSE
"Low Discount"
END

Types of Calculated Fields

   Type                              Example

Arithmetic                    Sales + Profit
Conditional                   IF-ELSE
Date                              YEAR(Order Date)
String                            UPPER(Name)
Aggregate                     SUM(Sales)
Logical                           AND, OR

Parameter vs Calculated Field

Feature           Parameter                   Calculated Field

Purpose           User Input                      Formula
Created By    User                            Formula
Dynamic           Yes                             Yes
Uses              Filters, Switching              Calculations

Parameters in Tableau

Punitha — Tue, 18 Aug 2026 04:00:07 +0000

What is a Parameters?

A Parameter is a dynamic value that allows users to change data, calculations, filters, or charts interactively.

Why Use Parameters?

Change calculations dynamically.
Create interactive dashboards.
Switch between charts.
Filter data.
Change measures (Sales, Profit, Quantity).

Example: Parameter for Sales and Profit

Suppose you have two measures:

Sales
Profit

Using a parameter, users can switch between:

Sales
or
Profit

How to Create a Parameter

Step 1: Open Tableau

Open Tableau and connect your dataset.

Step 2: Go to Data Pane

On the left side, right-click anywhere in the Data Pane.

Click:

Create Parameter

Step 3: Enter Parameter Details

Example:

Property               Value

Name                   Select Measure
Data Type              String
Allowable Values       List

Step 4: Add Values

Add values:

Sales
Profit
Quantity

Click OK.

Step 5: Show Parameter

Right-click the parameter.

Click:

Show Parameter

You will see:

Sales
Profit
Quantity

Create Calculated Field for Parameter

Go to:

Analysis → Create Calculated Field

Name:

Selected Measure

Formula:

CASE [Select Measure]

WHEN "Sales" THEN SUM([Sales])

WHEN "Profit" THEN SUM([Profit])

WHEN "Quantity" THEN SUM([Quantity])

END

Click OK.

Step 6: Use in Chart

Drag:

Category → Rows

Selected Measure → Columns

Now users can switch:

Sales
Profit
Quantity

The chart changes automatically.

Parameter Flow

Create Parameter
        ↓
Add Values
        ↓
Show Parameter
        ↓
Create Calculated Field
        ↓
Use in Chart
        ↓
Interactive Dashboard

Components of Tableau

Punitha — Mon, 17 Aug 2026 14:29:13 +0000

Worksheet

A Worksheet is where you create individual charts and visualizations.

Bar Chart

Line Chart

Pie Chart

Map

Table

KPI

Rows Shelf

The Rows Shelf is used to place fields that you want to display along the vertical direction.

Rows → Sales

Columns Shelf

The Columns Shelf is used to place fields that you want to display along the horizontal direction.

Columns → Category

Marks Card

The Marks Card is used to control the appearance of your visualization.

Color

Size

Label

Detail

Tooltip

Shape

Filters Shelf

The Filters Shelf is used to filter the data displayed in a visualization.

Filter → Region

East

West

North

South

Pages Shelf

The Pages Shelf allows you to view data step by step or as a sequence.

Pages → Year

Then view the visualization year by year.

Show Me

Show Me helps you quickly choose a suitable chart type.

Bar Chart

Line Chart

Pie Chart

Maps

Scatter Plot

Heat Map

Dashboard

A Dashboard combines multiple worksheets into one screen.

Dashboard
├── Total Sales Card
├── Sales by Category
├── Profit by Region
└── Sales Trend

Story

A Story combines multiple worksheets or dashboards to present data as a sequence.

Trends

Findings

Business insights

Data analysis