2024-04-16 06:03
In Spring,
you can create a thread pool using the TaskExecutor interface or its
implementations such as ThreadPoolTaskExecutor. Then, you can submit
asynchronous tasks to this thread pool to… Read More
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Tutorial on Java, Design Patterns, collections, Struts, jdbc
2024-04-16 04:24
Using DataFrameGroupBy.groups
attribute, we can get a dictionary-like view of the groups formed in groupby operation.
Exampledata = {'Name': ['Krishna', 'Chamu', 'Joel', 'Gopi', 'Sravya'… Read More
2024-04-16 04:24
Using ‘get_group()’
method of DataFrameGroupBy object, we can get a specific group details from the
grouped data based by its group name.
Exampledata = {'Name': ['Krishna', 'Ch… Read More
2024-04-16 04:21
Using ‘last()’
method of DataFrameGroupBy object, we can retrieve the last row from each group
based on the grouping criteria.
Exampledata = {'Name': ['Krishna', 'Chamu', 'Joel… Read More
2024-04-15 14:55
Time is a
fundamental aspect of programming, and in Java, it's essential to understand
the different units of time and how they relate to each other. Whether you're
working with nanoseconds… Read More
2024-04-15 14:50
Following
commands are used to configure title back ground color, border thickness etc.,
skinparam
titleBorderRoundCorner 25
skinparam
titleBorderThickness 3
skinparam
titleBorder… Read More
2024-04-15 14:50
You can
apply creol styles to customzie the diagram title.
creolTitle.txt@startuml
title
# Simple Login Flow example.
----
# Client enter //username and password//, submit to the LoginSer… Read More
2024-04-15 14:48
‘scale’
command is used to zoom the generated image. There are multiple ways to express
the scale.
Example
1: Express scale
factor as a number or fraction.
scale 2.5
scale 3… Read More
2024-04-13 15:57
Using
size() method of DataFrameGroupBy object, we can retrieve the number of
elements in each group. ‘size()’ method returns a Series that contains the
group names as the index… Read More
2024-04-13 15:54
Using ‘first()’
method of DataFrameGroupBy object, we can retrieve the first row from each
group based on the grouping criteria.
Exampledata = {'Name': ['Krishna', 'Cham… Read More
2024-04-13 15:51
Using ‘len’
function, we can get the number of groups in DataFrameGroupBy object.
Examplegroup_by_city = df.groupby('City')
group_by_gender_city = df.groupby(['Gender', 'City'… Read More
2024-04-12 04:10
Using
@startmath/@endmath, we can create standalone AsciiMath formula.
asciiMath.txt@startmath
sum_(i=1)^n i^3=((n(n+1))/2)^2
@endmath
Above
snippet generat… Read More
2024-04-12 04:09
We can
create standalone JLaTeXMath formula using @startlatex/@endlatex.
latexMath.txt@startlatex
\sum_{i=0}^{n-1} (a_i + b_i^2)
@endlatex
Above
snippet generate… Read More
2024-04-12 04:06
Using
styleTag.txt@startyaml
#highlight "name"
#highlight "address" / "city"
#highlight "hobbies" / "1"
#highlight "emails" / "0" / "id"
id: 1
name: Krishna
address:
state: Karnatk… Read More
2024-04-11 15:35
Documentation
is a crucial aspect of coding, providing insights into the purpose and
functionality of various methods and properties. However, maintaining clear and
concise documentation can… Read More
2024-04-11 14:42
Using to_csv()
method, we can To export data from a Pandas DataFrame to a CSV ((Comma-Separated
Values) file.
Example
1: Write dataframe to
csv file
df.to_csv('/Users/Shared/csv/demo1.cs… Read More
2024-04-11 14:41
In this
post and coming subsequent posts, I am going to explain the group by operations
on DataFrame.
What is
Group By operation?
Group By
operation is used to group rows based on one or… Read More
2024-04-11 14:36
Using the
read_csv() method from the Pandas library, we can read the data from an url.
Exampledf = pd.read_csv(url)Find the
below working application.
read_from_url.py
import… Read More
2024-04-10 15:47
In
software development, particularly in Java, there are situations where case
sensitivity in data lookups can be a trouble. Consider scenarios where you need
to retrieve values from a colle… Read More
2024-04-10 15:00
The java.util.ServiceLoader
class in Java provides a simple mechanism for discovering and loading
implementations of a service interface from the classpath. It is part of the
Java Standard L… Read More
2024-04-10 04:05
We can
visualize the yaml document using PlantUML.
helloworld.txt@startyaml
id: 1
name: Krishna
address:
state: Karnatka
city: Bnagalore
country: India
hobbies:
- Playing cri… Read More
2024-04-10 04:04
Using
#highlight directive, we can highlight some parts of the yaml document.
Example#highlight "name" : Highlight name property
#highlight "address" / "city" : Highlight city property i… Read More
2024-04-10 04:01
Using
styleTag.txt@startjson
#highlight "name"
#highlight "address" / "city"
#highlight "hobbies" / "1"
#highlight "emails" / "0" / "id"
{
"id" : 1,
"name" : "Krishna",
"address"… Read More
2024-04-10 03:46
The
Arrays.deepToString() method is a utility method provided in the java.util
package in Java. It's used to generate a string representation of nested
arrays.
When you
pass a multi… Read More
2024-04-09 05:43
A stack is
a fundamental data structure in computer science that follows the Last In,
First Out (LIFO) principle. Imagine a stack of plates where you can only add or… Read More
2024-04-09 03:39
Using
swaplevel() method, we can swap the index levels in a multi index data frame.
Let’s use below data set to demonstrate the
examples. Name Age City Gender Rating… Read More
2024-04-09 03:38
In this
post, I am going to explain how to reshape the dataframe using pivot method.
Signature
DataFrame.pivot(index=None,
columns=None, values=None)’
Following
tabl… Read More
2024-04-09 03:34
In this
post, I am going to explain how to extract the row from a multi index data
frame using ‘loc’ accessor.
Let’s use below data set to experiment with the
examples… Read More
2024-04-08 04:40
In Java,
copying data from an InputStream to an OutputStream is a common task,
especially when dealing with file operations, network communications, or
handling HTTP requests. In this blog p… Read More
2024-04-08 03:45
PlantUML
helps you to visualize the JSON data.
helloworld.txt@startjson
{
"id" : 1,
"name" : "Krishna",
"address" : {
"state" : "Karnatka",
"city" : "Bnagalore",
"country" : "In… Read More
2024-04-08 03:44
Using
#highlight directive, we can highlight some parts of the json document.
Example#highlight "name" : Highlight name property
#highlight "address" / "city" : Highlight city property i… Read More
2024-04-08 03:42
You can
customiae the color, font styles using
styleTag.txt@startuml
skinparam backgroundColor LightBlue
left to right direction
state state1
state state2
state state3
state state… Read More
2024-04-06 06:18
Using get_level_values()
method we can retrieve the values of a specific level from a multi-indexed
DataFrame.
Let’s use
following data set to experiment with the examples. Year… Read More
2024-04-06 06:17
There are
two ways to customize the multi-level index names.
a.
Updating
the index.names property
b.
Using
index.set_names method
Let’s experiment wi… Read More
2024-04-06 06:11
‘df.index.names’
return list of column names involved in a multi index.
Example
multi_index_column_names
= df.index.names
multi_index_column_names.pyimport pandas as… Read More
2024-04-05 15:41
HTTP/2,
commonly pronounced as "http two," marks a notable advancement in the
Hypertext Transfer Protocol (HTTP), the backbone of communication between web
servers a… Read More
2024-04-05 10:53
Spring boot 3 : Hello World rest application Read More
2024-04-05 10:52
In this
post, I am going to explain how to create a hello world rest application using
spring boot3.
Prerequisites
Java17
Maven 3.5
or higher (I tested the app with maven 3.8.4)
… Read More
2024-04-05 09:47
In Java
programming, handling date and time values is a fundamental aspect of many
applications. Whether it's displaying dates in a specific format, parsing user
input, or manipulating tempo… Read More
2024-04-05 05:26
Using
sort_index method, we can sort a multi indexed data frame.
Let’s experiment with the below data set. Year Quarter Sales City
0 2022 1 100 Bangalore
1… Read More
2024-04-05 04:06
In this
post, I am going to explain how to recognize faces using OpenCV built-in face
recognizer.
You can
download this example from below link.
https://github.com/harikrishna553/p… Read More
2024-04-04 11:31
In this
post, I am going to explain how to read videos in OpenCV. Videos in OpenCV are
read frame by frame. Follow below step-by-step procedure to read the video.
Step 1:
Import ope… Read More
2024-04-04 11:31
We can
resize the video by resizing the video frame by frame.
Following snippet resize the frame or image.def resize_frame(frame, scale_width=0.5, scale_height=0.5):
width = int(frame… Read More
2024-03-17 06:09
In this
post, I am going to use Haar Cascade Classifiers, to detect the faces in an
Image. Haar Cascade Classifiers are machine learning models that have been
trained to recognize specific o… Read More
2024-03-12 10:27
One of the
ways to classify databases is by how the data is stored on disk: row- or
column-wise. Tables can be partitioned either horizontally (storing values
belonging to the same row toget… Read More
2024-03-12 06:44
Using #color
notation, we can apply colors to the state diagram.
inlineColor.txt@startuml
left to right direction
state state1 #FF9876
state state2 #lightblue
state state3 #palegreen
st… Read More
2024-03-12 06:44
customizeUsingSkinParam.txt@startuml
skinparam backgroundColor LightBlue
skinparam state {
StartColor PaleGreen
EndColor brown
BackgroundColor gold
BackgroundColor aqua
BackgroundColo… Read More
2024-03-12 06:39
Using
‘note on link’ command, we can put notes on the links.
Example 1state1 --> state2
note on link : This is note 1
Example 2
: multi line note… Read More
2024-03-12 06:29
Durability
in ACID and DBMS means that once you finish a transaction, the changes you made
to the database persist always even if something goes wrong with the compu… Read More
2024-03-10 06:59
SkipList
is a specialized form of a Linked List optimized for rapid search and insertion
operations.
In
SkipLists, both insertion and search tasks are accomplished with a time
compl… Read More
2024-03-09 10:56
Database
systems are classified into two main categories: in-memory and disk-based,
based on how they store and manage data.
In-memory
databases
In-memory… Read More
2024-03-09 08:09
Volatile
Memory
Both
volatile and non-volatile memory are super important in computers. Volatile
memory is like a sticky note - it holds information temporarily and… Read More
2024-02-28 15:18
Using
histogram, we can visualize the distribution on pixel intensities in an image.
Using cv2.calcHist
method, we can compute histogram from an image or specific portion of the
ima… Read More
2024-02-27 04:59
Using
‘str.split()’ method, we can split the text content of a DataFrame column.
I am using following data set to demonstrate the
examples. Name Age City… Read More
2024-02-27 04:58
Multi
indexing is a feature, where we have multi levels of indexing to get better
performance while processing the data.
I am using
below data set to demonstrate the example. Yea… Read More
2024-02-14 09:00
Multi-level
indexing, often referred to as B-tree indexing, is a hierarchical data structure
used in databases for efficiently finding particular records. This approach is
invaluable for ext… Read More
2024-02-14 07:22
Indexing
in databases is like using a book's index to find information quickly. Instead
of searching every page, you just look up a word in the index and go straight
to the page you need.
… Read More
2024-02-13 05:34
Using
histogram, we can visualize the distribution on pixel intensities in an image.
Using cv2.calcHist
method, we can compute histogram from an image or sp… Read More
2024-02-13 05:34
In this
post, I am going to explain how to extract specific portion of the image using
masking technique.
Following
snippet is used to extract the image of intrest using masking tec… Read More
2024-02-13 04:17
Data
governance refers to the system and practices an organization uses to
effectively manage its data. It covers everything from establishing rules and
standards to ensure only author… Read More
2024-02-12 12:03
Data
inventories and data catalogs share a close connection, but they aren't exactly
alike. Here's a breakdown of their main differences:
Data
Inventory:
D… Read More
2024-02-12 12:03
Data
catalog serves as a centralized repository for metadata about all datasets
within an organization. Even though its main job isn't to directly related to
data quality, it can really help… Read More
2024-02-12 10:44
No, a data
catalog doesn't keep the actual data itself. It's more like a library index for
all your organization data sets. For example, a data catalgo for a library
shows you what books are… Read More
2024-02-12 10:30
The key
stakeholders of a data catalog can be vary depending on the organization, but
usually include:
1. Data
Analysts: These folks
study past data to answ… Read More
2024-02-12 10:15
Imagine a
data catalog as a giant directory, kind of like the index at the back of a
book. It's like a big library where you can find details about all the
different types of data used… Read More
2024-02-12 06:18
Data
lineage can be categorized into several types based on the granularity, scope,
and purpose of the lineage information. Understanding these different types of lineages
help the org… Read More
2024-02-12 06:18
Forward
lineage traces the path of data from its origin to the destination. It provides insights into how data flows through various processes and
transformations, h… Read More
2024-02-12 06:17
Backward
data lineage, refers to the procedure of tracking data elements from the destination
(like a report or dashboard) back to the original source. It stands in contrast
to conventional… Read More
2024-02-12 06:15
Operational
lineage is instrumental in tracking the execution history of data processes,
providing insights into runtime, frequency, and performance metrics. This type
of lineage aids in mon… Read More
2024-02-12 06:10
Physical
lineage delves into the granular technical details of data movement, offering a
comprehensive view of how data traverses through various hardware and softwa… Read More
2024-02-12 06:02
Business
lineage provides a business-centric perspective on the movement of data,
abstracting technical details to offer a clear understanding of how
information flo… Read More
2024-02-12 05:57
End-to-end
lineage offers a comprehensive view of data movement and transformation across
all stages of its lifecycle, from the initial data source to its final
dest… Read More
2024-02-12 05:53
Process-level
lineage outlines the sequence of processing steps or transformations that data
undergoes, without necessarily going into the details of field or table-level
changes. It helps i… Read More
2024-02-12 05:45
Table-level
lineage provides a higher-level view, focusing on how entire tables or files
move and transform from one system to another. This type is beneficial for
understanding the relation… Read More
2024-02-12 05:43
Field-level
lineage is like tracing the journey of each column or field information in the
entire data lineage process. It helps us to see exactly how the data in one
column or field gets cr… Read More
2024-02-12 05:33
Answering
the question of which downstream processes or systems consume data is crucial
for several key reasons:
1.
Dependency
Management:
Under… Read More
2024-02-12 05:20
Data lineage refers to the tracking of data from its origin through its various transformations and movements across different stages of processing, analysis, and consumption within an… Read More
2024-02-12 05:19
Understanding
how data has been modified or enriched along its journey is essential for
several reasons:
1.
Data
Transformation Analysis:
Tracki… Read More
2024-02-12 05:13
Understanding
where data originated from is crucial for several reasons:
1.
Data
Provenance: Knowing
the source of data is essential for establi… Read More
2024-02-08 01:27
Approach
1: Writing custom
function.
pretty_print_dictionary.pydef pretty_print_dict(dict, indent=0):
for key, value in dict.items():
if isinstance(value, dict):
p… Read More
2024-02-08 01:13
Example
state1
-[dotted,#blue,thickness=10]-> state2
arrowColorStyleThickness.txt@startuml
[*] --> state1
state1 -[dotted,#blue,thickness=10]-> state2
state2 -down[dashed… Read More
2024-02-08 01:12
Using
below keywords, we can add notes to the activities in an activity diagram.
a.
note
left of
b.
note
right of
c.
note
top of
d. &hell…Read More
2024-02-08 01:08
Using up,
down, left and right keywords we can force the arrow direction between states.
arrowDirection.txt@startuml
[*] --> state1
state1 -right-> state2
state2 -down-> s… Read More
2024-02-07 04:55
Approach
1: Using split method
In Python,
the split() method is typically used to divide a string into substrings. It
operates by breaking the string at designated separators and returns a… Read More
2024-02-07 04:11
The ‘setdefault()’
method is a dictionary method in Python that checks for a key's existence and
assigning a default value if the key is not exists in the dictionary.
I… Read More
2024-02-07 03:48
In a
pandas DataFrame, the index property represents the row labels or index labels
of the DataFrame.
df.index =
df.index.str.upper()
Above
snippet convert all the row labe… Read More
2024-02-07 03:48
In a
pandas DataFrame, the columns property represents the column names of the
DataFrame.
df.columns
= df.columns.str.strip().str.upper()
Above
snippet convert all the colu… Read More
2024-02-07 03:46
Using
strip(), lstrip(), rstrip() methods we can remove the whitespaces in given
column values.
a.
strip():
Remove leading and trailing whitespace from the given column… Read More
2024-02-06 12:25
The Token
Bucket Algorithm helps to control the rate at which requests are made to a
system or server. It works by simulating a bucket with a limited number of
token… Read More
2024-02-06 04:16
Using ‘cv2.mege’
method, we can merge individual color channel images to single channel image.
Signature
dst =
cv2.merge(images)
images: It
is a list of indivi… Read More
2024-02-06 04:15
You can
perform Bitwise operations at pixel level. Following bitwise operators are used
in common.
a.
not
b.
and
c.
or
d.
xor
 &hell…Read More
2024-02-06 04:03
Using
‘cv2.split’ method, we can split the multi-channel image into individual color
channel images.
Signature
dst =
cv2.split(image[, mv])
image:
Specifies th… Read More
2024-02-05 08:39
Using both
values() method and ‘in’ operator, we can check for the existence of a value in
a Dictionary.
Retrieve
the values from the dictionary:
Use the
values() method to ob… Read More
2024-02-05 06:56
Event
sourcing is a way of organizing data in a computer system. Instead of keeping
track of the current state directly, it stores a series of events that show how
the system changed over ti… Read More
2024-02-05 04:33
>
and > stereotypes are used to define entry and exit
points.
Example
state
entry1 >
state
exit1 >
entryAndExitPoints.txt@startuml
left to right direction
s… Read More
2024-02-05 04:33
>
and > stereotypes are used to add expansion
points.
expansionPoints.txt@startuml
left to right direction
state MyState{
state state1
state state2
state state3
state entry… Read More
2024-02-05 04:30
>
stereotype used to define conditional state.
conditionalState.txt@startuml
state init
state someCondition >
state "less utilized resources" as lur
state "high utilized resources"… Read More
2024-02-02 01:46
'startswith'
method can be applied on a DataFrame column to check whether particular value
starts with given string or not.
Examplename_starts_with_k = df['Name'].str.lower().str.st… Read More
2024-02-02 01:46
'endswith'
method can be applied on a DataFrame column to check whether particular value
ends with given string or not.
Examplename_ends_with_a = df['Name'].str.lower().str.endswith… Read More
2024-02-02 01:43
Using
contains() method, we can filter the data frame rows based on given sub string
presences.
Example
1: Filter rows when
the column value contain given substring.book_in_hobbies… Read More
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