Interesting


great


grear


The House of Representatives in Nigeria has advanced a bill for the establishment of state police to the second reading. Sponsored by the Deputy Speaker, Ben Kalu, and 14 others, the bill aims to transfer "Police" from the "Exclusive Legislative List" to the "Concurrent Legislative List," granting states control over policing. It proposes 16 alterations to the constitution, including the establishment of State Police Service Commissions and provisions for federal support in funding state police forces. Proponents argue that decentralizing law enforcement is essential for addressing local security challenges effectively. Despite past opposition due to concerns about potential abuse by governors, the bill received widespread support during the debate, with lawmakers emphasizing the need for a tailored, community-centric policing system. The bill will undergo further legislative processes before potentially becoming law.

https://media.premiumtimesng.com/wp-content/files/2024/02/Police-1140x570.jpg


10. Binance, a leading cryptocurrency exchange, has announced the discontinuation of support for several leveraged token services, including those linked to Bitcoin and Tether. Trading and subscription services for these tokens will be suspended on February 28, 2024, with all trade orders automatically removed at that time. Users are advised to convert their holdings into other assets before the deadline. Starting April 1, Binance will gradually delist and cease redemption of the tokens. If users fail to redeem their tokens by the deadline, Binance will convert them into USDT based on their value on the delisting date and distribute them to users' accounts within 24 hours. Binance's leveraged tokens provide investors with leveraged exposure to crypto assets without requiring collateral or maintenance margin levels, but the exchange warns of associated risks, including price movements in the perpetual contracts market.


9. The United States Attorney’s Office for the Southern District of Florida has charged Adam Todd, the CEO of Digitex Futures Exchange, with intentionally causing his company to violate the Bank Secrecy Act. Todd allegedly operated Digitex as an unregistered crypto futures trading platform from January 2018 to April 2022, failing to implement adequate anti-money laundering (AML) and know-your-customer (KYC) programs. This indictment follows a default judgment issued by the Commodities Futures Trading Commission (CFTC) against Todd last year for manipulating the price of Digitex's native token, DGTX. If convicted, Todd faces up to five years in federal prison and will be sentenced by a federal district court judge. Additionally, the court imposed a permanent injunction, disgorgement, and civil monetary penalty on Todd and his companies in the CFTC's enforcement action.


South Korea's ruling People Power Party is pushing for a two-year postponement on cryptocurrency taxation, aligning with their campaign pledges for the upcoming elections. The party emphasizes the need for a robust regulatory framework before implementing taxation, citing risks and the absence of a regulatory structure akin to stock exchanges. The proposed extension aims to allow time for necessary amendments and the establishment of comprehensive regulations. But then, discussions within South Korea's legislative body hint at potential reforms to harmonize crypto taxation thresholds with stocks, aiming for a more equitable tax framework. Additionally, recent policies mandate high-ranking officials to disclose cryptocurrency holdings to uphold ethical standards. The party's stance contrasts with the government's broader initiative to eliminate taxes on various financial investments, including stocks and funds, signaling ongoing debates surrounding crypto taxation reform in South Korea.


Asian nations, particularly Japan and South Korea, are intensifying efforts to enhance oversight and consumer protection in the cryptocurrency market. Japan's Financial Services Agency (FSA) proposes measures to prevent "unlawful transfers" to crypto exchanges, potentially impacting peer-to-peer transactions. South Korea's Financial Intelligence Unit (FIU) plans to tighten scrutiny by implementing a pre-emptive trading suspension system for suspicious transactions and expanding its crypto team. Meanwhile, the European Parliament moves forward with the AI Act, aiming to regulate artificial intelligence across various sectors and establish safeguards against potential threats to citizens' rights.


Y Combinator, a prominent Silicon Valley incubator, has highlighted stablecoins, metaverse technologies, and artificial intelligence (AI) solutions as key areas for startup innovation. Stablecoins are seen as transformative in cross-border payments, akin to the evolution of digital music. The potential for growth is significant, given the large population in countries with high inflation rates. AR and VR technologies are envisioned to extend beyond gaming, with recent advancements indicating progress. AI holds promise in customizing enterprise software and automating back-office processes, although addressing biases remains a challenge. Y Combinator's focus underscores the importance of these sectors in driving innovation across various industries.


The United Kingdom is moving towards enacting legislation to regulate stablecoins and crypto staking, aiming to accomplish this goal within the next six months. Economic Secretary to the Treasury, Bim Afolami, emphasized the government's commitment to passing these laws before the upcoming general election during a recent crypto event hosted by Coinbase in London. While details remain scarce, Afolami assured that efforts are underway to expedite the process. This initiative aligns with Prime Minister Rishi Sunak's vision to position the UK as a "global crypto hub," fostering an environment conducive to investment, innovation, and scaling within the crypto sector. Despite previous pledges, progress on crypto regulation has been limited, prompting calls from industry players for clearer guidelines. The government signaled its intent to introduce crypto-specific regulations in 2024, including oversight of fiat-backed stablecoins by the Financial Conduct Authority (FCA).


Napoli has decided to part ways with head coach Walter Mazzarri, only three months into his tenure. Despite his previous experience with Watford, Mazzarri managed just six victories in 17 games, leaving Napoli in ninth place in the Serie A table following a disappointing 1-1 draw against Genoa. To steer the team for the remainder of the season, Francesco Calzona, currently managing the Slovakia national team, will take the helm. Calzona will juggle both roles, guiding Napoli while also preparing Slovakia for the upcoming European Championships in Germany. Mazzarri's departure marks Napoli's third coaching change this season, following Rudi Garcia's short-lived stint after replacing Luciano Spalletti, who departed after clinching the club's first league title in 33 years.


FG, Cement manufacturers agree on N7,000 to N8,000 for 50kg per bag

The Federal Government of Nigeria and Cement Manufacturers have agreed on a N7,000 to N8,000 per 50 kg bag of cement to halt the astronomical rise in the price of the product. The price hike is linked to the astronomical inflation rate biting hard in the country and partly due to the Federal Government’s decision to now build concrete roads in place of asphalt.


GIRONA OUT OF STEAM?
It seems like Girona's strong performance at the beginning of the 2023/2024 Laliga season has taken a hit in the second leg. Despite their initial fight to stay at the top alongside Real Madrid, recent matches have seen them losing momentum. In the last three games alone, Girona has dropped a total of 8 points. As a result, Real Madrid has pulled ahead, now leading by a clear margin of 6 points.


Mr. Olabode Olawuyi, veterinary technologist, who has been in charge of the Zoological Garden for over a decade at Obafemi Awolowo University, was attacked on Monday afternoon, 19th February, 2024, by a 9-year-old male lion when he was feeding them in their den at the Zoological Garden of the University. Mr Olawuyi has been taking care of the lions since they were born on campus about 9 years ago but, tragically, the male Lion killed the man who had been feeding them.


This is massive


Wow! This is great indeed.


Quite interesting


It appears to but we wait to see.


That is great to note.


This is really important


this is helpful, thanks.


Very important


This is true.


### Introduction
Exploratory Data Analysis (EDA) is considered a pillar in data science and data analysis. Usually represented in graphs, plots and summary statistics, it is aimed at uncovering insights in your data.

Fortunately, pandas is a powerful library that comes with a lot of functions, methods and commands that makes data exploration simple.

Here is a curated list of some ways you can use pandas for Exploratory Data Analysis:

##### 1. Loading the Data

-----------

```
# Import the pandas library
import pandas as pd

# Read data from a CSV file
df = pd.read_csv('filename.csv')

# Read data from an Excel file
df = pd.read_excel('filename.xlsx')

```

##### 2. Viewing Data:

-----------

```
# Display the first few rows of the DataFrame
df.head()

# Display the last few rows of the DataFrame
df.tail()

# Display additional information about the DataFrame
df.info()

# Display summary statistics of numerical columns
df.describe()

```

##### 3. Basic Information:

-----------

```
# Number of rows and columns
df.shape

# Column names
df.columns

# Data types of each column
df.dtypes
```

##### 4. Handling Missing Values:

-----------

```
# Check for missing values
df.isnull().sum()

# Drop rows with missing values
df.dropna()

# Fill missing values with a specified value
df.fillna(value)

```

##### 5.  Filtering and Selection:

-----------

```
# Select specific columns
df[['column1', 'column2']]

# Filter rows based on a condition
df[df['column'] > value]

# Select rows and columns by label
df.loc[row_label, column_label]
```

##### 6. Grouping and Aggregation:

-----------

```
# Group by a column and calculate mean
df.groupby('column').mean()

# Group by multiple columns and calculate sum
df.groupby(['col1', 'col2']).sum()
```

##### 7. Sorting Data:

-----------

```
# Sort by a single column
df.sort_values('column')

# Sort by multiple columns
df.sort_values(['col1', 'col2'])
```

##### 8.  Creating New Columns:

-----------

```
# Create a new column based on existing columns
df['new_column'] = df['col1'] + df['col2']

# Apply a function to create a new column
df['new_column'] = df['column'].apply(function)
```

##### 9. Visualization:

-----------

```
# Plotting a histogram
df['column'].hist()

# Plotting a scatter plot
df.plot.scatter(x='col1', y='col2')
```

##### 10. Combining DataFrames:

-----------

```
# Concatenate DataFrames vertically
pd.concat([df1, df2], axis=0)

# Merge DataFrames based on a key
pd.merge(df1, df2, on='key_column')
```

### Conclusion
These are just a few examples of pandas commands for data exploration. Depending on your specific analysis, you may need to use additional functions and techniques provided by pandas. The pandas documentation is a valuable resource for exploring more functionalities: [Pandas Documentation.](https://pandas.pydata.org/pandas-docs/stable/)

10 Powerful Pandas Commands for Exploratory Data Analysis

Get a jump-start to Exploratory Data Analysis using one of the most powerful libraries - pandas!


A draft to delete


On March 29, 2022, all of Nigeria was utterly disappointed with the scoreline between Nigeria and Ghana which meant that Nigeria was going to miss the 2022 World Cup tournament at Qatar. While the pains of missing on that world still hunt most football enthusiasts in the country, the Super Eagles where off to another disappointing start to the 2026 World Cup qualifier. On Thursday, November, 16, 2023, the Super Eagles had to come from behind to settle on a 1-1 draw at home to Lesotho. The same thing happened on Sunday, November, 19, 2023 at the Huye Stadium, Rwanda, when they played Zimbabwe.

The results meant that Nigeria is second on the log to South Africa who had won their first game against Benin republic and has a game at hand. A back-to-back draw against Lesotho and Zimbabwe in the 2026 World Cup qualifier suggests that Nigeria has faced some challenges in securing victories in these particular matches. Although, drawing two matches is not necessarily an indication of a World Cup miss but they will need to win all their upcoming matches to be guaranteed a spot at the biggest footballing event in the world.

Spectators have been critical of the coach, Jose Peseiro who was appointed on the heels of the sack of Gernot Rohr, on whose hands, the Super Eagles lost the spot to the Black Stars of Ghana. Nigeria has some of the most in-form attackers in world football right now but this has not resulted in anything meaningful for the nation’s team. Will the head coach turn around the fortunes of the nation’s team or will Nigeria Football Federation (NFF) show the Portuguese the way out remains to be seen even as reports suggest that the head coach is among candidates jostling for the vacant position at Zamalek SC, an Egyptian club.

Another person that has received the heat of criticism is the man between the sticks for the super eagle, Francis Ozoho. Ozoho has received the support of the head coach but he has not been able to establish himself in the hearts of the fans.
The Africans Cup of Nations will kickstart in January 2024. With this performance, are the super eagles ready for the tournament even? These and many more are questions in the minds of football enthusiasts and the days ahead could be defining for the three-time African champions.

Nigeria’s back-to-back draw to Lesotho and Zimbabwe in the 2026 World Cup qualifier; a signal for back-to-back World Cup miss?

After two straight draws in the qualifier, will Nigeria miss the next World Cup ?


Data is now recognized as the new oil for its role in shaping business decisions of organizations. It is a critical resource that when harnessed effectively, can power and drive various aspects of organizations, governments and societies. It is reckoned with to provide insights to business outlook. This has rapidly increased the number of data science enthusiasts and practitioners.

Data scientists concern themselves with building models that can be used to support these decisions. However, as Cathy O’Neil argues in the 2016 book “Weapon of Math Destruction,” certain mathematical models and algorithms when used without proper oversight and accountability can lead to unfair and even harmful consequences. Math Destruction therefore refers to the negative potential consequences or unintended harm that can arise from the misuse or misapplication of mathematical models particularly in the field of data science.

**Best Practices**
It is therefore imperative to have a set of best practice rules to guide against these situations. The list is inexhaustive but here I explained a few which I consider paramount:
**1.	Understand the problem at hand:** No surprises here. Knowing the problem is half solving it. Before doing anything, your first task is to understand the problem you are trying to solve. This helps in framing the right questions and selecting relevant data.
**2.	Understand the data you have:** This calls for Exploratory Data Analysis. There are several ways to explore your data including visualization, checking missing values, outliers, anomalies, etc.
**3.	Data cleaning and preprocessing:** This is usually where the bulk of your work as a data scientist lie. This involves cleaning the data and preparing it for analysis. The importance of this step cannot be over-emphasized as it can significantly affect the quality of your model.
**4.	Feature engineering:** Often times, you use one more feature in your dataset to make prediction. It is in this step that you create meaningful features that enhance the predictive power of your model. This step may include creating new features, transforming existing ones or selecting the most relevant ones for data modelling.
**5.	Choose appropriate model:** Having understood the problem at hand, you choose the appropriate model that fits it. The characteristics of your data, the type of problem you are trying to solve and its interpretability are all factors you consider when choosing the right model.
**6.	Hyperparameter Tuning:** Sometimes your model may lack generalization or it can be overfitting. That means it will not perform well on data it has not seen. Therefore, you need to optimize some parameters to achieve better performance.
**7.	Model validation and Evaluation:** This is another crucial step to be taken. It is necessary to assess how your model will generalize to new and unseen data.
**8.	Result communication:**  Clearly communicate your findings to relevant stakeholders using appropriate tools such as visualization and storytelling.
**9.	Ethical considerations:** It is not enough to just build models, it is equally important to be vigilant about biases in your models.

Escape "Math" Descruction with Best Practices in Data Science


I want to join the Buidlers monthly magazine creation activity — This is a comment on: https://yakihonne.com/article/naddr1qq2kucmt89n4wvjfx4rryd6l94n565jhxf8ksq3qyzvxlwp7wawed5vgefwfmugvumtp8c8t0etk3g8sky4n0ndvyxesxpqqqp65wnkefak


**Introduction**
Whether you are just starting out or you have years of experience as a data professional, data visualization is a crucial tool for gaining insight from your data. These insights are presented visually so that you can easily see the trends, patterns and connections in your data. Matplotlib is one of the most popular and versatile libraries for creating data visualization.

In this article, we will cover the following:

1. Installing and Importing Matplotlib
2. Components of Matplotlib
3. Creating Basic Plots
4. Customizing Plots

**Prerequisites**
While a basic understanding of python is recommended, you can also follow along if you are new to the programming language. We shall use jupyter notebook to show the step by step process for visualizing your data. Here is a [link ](https://www.anaconda.com/download/) to download and install Anaconda, a jupyter notebook can be found inside it.

**Installing and Importing Matplotlib**
To use Matplotlib, you need to install it first. You can use Python’s standard package manager ’pip.’ Open your jupyter notebook and run the following command:
`pip install matplotlib`

This command will download the latest Matplotlib from Python Package Index (PyPI) and install it on your computer. After the installation is complete, you can import Matplotlib into your Jupyter notebook 	using the following code:
`import matplotlib.pyplot as plt`

**Components of Matplotlib**
Matplotlib has several components; a few of them are:

1. Figure: This is a container which holds all the elements of a plot.
2. Axes: This is the part of the page that holds the data to be displayed. A plot can contain one or more axes.
3. Axis: These are X and Y axes (plural of axis) with tick marks and labels that allow you to understand the data values corresponding to the points in the plot.

**Creating Basic Plots**
We can create a basic plot of some data points using the example below:

```

```

```
# Import matplotlib module
import matplotlib.pyplot as plt

# Create a figure and an axes
fig, ax = plt.subplots()

# Sample data to be plotted
years = [2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]
population = [9872, 9912, 10098, 11208, 12289, 13897, 13991, 14583, 16721, 17210]

# Plot the data on the axes
ax.plot(years, population)

# Add labels and a title
ax.set_xlabel('Year')
ax.set_ylabel('Population (millions)')
ax.set_title('Population Growth Over Time')

# Show the plot
plt.show()
```

```

```

In the above code snippet, we first imported the matplotlib module, then we created a figure and an axes. The years and population variables hold the data to be plotted. Typically, this data comes from your database records or an external source. ax.plot(years, population) is used to plot the data on the axes. We then set the X and Y axis labels and title to the plot, and finally display it with plt.show().

The plot created is display below:
![image](https://yakihonne.s3.ap-east-1.amazonaws.com/c07dc7ccd9e3e8649e677845d36e477e6899915f5993829d29311bed552d19a4/files/1696272412972-YAKIHONNES3.png)

**Customizing Plots **
You can customize the appearance of your plot by adding features like markers, color, linestyle and grid lines.

```
# Import matplotlib module
import matplotlib.pyplot as plt

# Create a figure and an axes
fig, ax = plt.subplots()

# Sample data to be plotted
years = [2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]
population = [9872, 9912, 10098, 11208, 12289, 13897, 13991, 14583, 16721, 17210]

# Plot the data on the axes
ax.plot(years, population, linestyle ='-', marker='v', color='b')

# Add labels and a title
ax.set_xlabel('Year')
ax.set_ylabel('Population (millions)')
ax.set_title('Population Growth Over Time')

# Show the plot
plt.grid(True)
plt.show()
```
![image](https://yakihonne.s3.ap-east-1.amazonaws.com/c07dc7ccd9e3e8649e677845d36e477e6899915f5993829d29311bed552d19a4/files/1696272515221-YAKIHONNES3.png)
The type of plot to be used is determined by the kind of data and the insights to be derived from it. The following are some common types of plots and the kinds of data that suits them:

1. Line plot: This is most suitable for time series and continuous data and is used to display trends over time, compare multiple datasets, and show continuous data points.
2. Bar plot: Bar plots are recommended for categorical data (nominal or ordinal).
3. Scatter plot: This is used for two continuous variables to show the correlation or relationship between them.
4. Pie chart: This is used for categorical data to show the relative proportion of different categories.
5. Heatmap: Heatmap is best used for two-dimensional data to visualize relationships between two variables and to identify patterns in matrices.
6. Box plot (Box-and-Whisker Plot): This is used for continuous data to display the distribution of data including quartiles, and detect outliers.

As a general rule, consider the nature of your data, the relationship you want to establish, and the message you want to communicate when selecting a plot type.  For starters, you may want to experiment with different types of plots to find the one that best fits your specific analysis.

Gain Mastery of Data Visualization Using Matplotlib in Simple Steps

A Beginner’s Guide to Understanding the Secret to Gaining Business Insights


Imposter Syndrome, also known as impostor phenomenon, is a psychological pattern in which individuals doubt their accomplishments and have a persistent fear of being exposed as frauds despite evidence of their competence. It's a phenomenon that can affect professionals across various fields, including the IT industry.

In the context of IT experts, Imposter Syndrome manifests when individuals working in technology-related roles, such as developers, engineers, or IT managers, believe that their skills and knowledge are inadequate, and they attribute their successes to luck or external factors rather than their abilities.

Symptoms
Imposter Syndrome can manifest in various ways among IT experts:
1.	Self-Doubt: IT professionals with imposter syndrome often doubt their abilities, questioning whether they are truly competent in their roles.
2.	Fear of Exposure: There's a constant fear of being "found out" as someone who doesn't belong in the field, leading to anxiety and stress.
3.	Overcompensation: Some individuals may overwork or strive for perfection to compensate for their perceived shortcomings, leading to burnout.
4.	Comparison: IT experts with imposter syndrome tend to compare themselves to their colleagues, believing that others are more knowledgeable or skilled.
5.	Difficulty Accepting Praise: They may struggle to accept compliments or recognition for their work, believing that they don't deserve it.

Effects
The effects of imposter syndrome can be profound and detrimental for IT experts:
1.	Stagnation: It can hinder professional growth and development as individuals may avoid new challenges and opportunities.
2.	Burnout: The constant pressure to prove oneself can lead to burnout and negatively impact mental and physical health.
3.	Reduced Confidence: Imposter syndrome erodes self-confidence, making it difficult to make decisions and contribute effectively to projects.
4.	Isolation: Individuals may withdraw from colleagues and support networks, fearing that they'll be "exposed."

Remedy
Overcoming imposter syndrome is possible with the right strategies:
1.	Self-Awareness: Recognize and acknowledge that you're experiencing imposter syndrome. Understand that it's a common phenomenon.
2.	Talk About It: Share your feelings with trusted colleagues, mentors, or a therapist. Talking about your experiences can help you gain perspective.
3.	Track Achievements: Keep a record of your accomplishments and positive feedback to remind yourself of your competence.
4.	Set Realistic Goals: Break down your goals into smaller, achievable steps. Celebrate each success along the way.
5.	Challenge Negative Thoughts: Challenge self-critical thoughts and replace them with more positive and realistic ones. Use positive affirmations.
6.	Seek Mentorship: Find a mentor who can provide guidance, support, and reassurance in your professional journey.
7.	Practice Self-Care: Prioritize self-care activities such as exercise, meditation, and hobbies to reduce stress and build resilience.
8.	Continual Learning: Embrace lifelong learning and stay updated in your field. Knowledge and skill acquisition can boost confidence.

Conclusion
Imposter syndrome is a common experience among IT experts, but it doesn't have to define your career. By recognizing the symptoms, understanding its effects, and implementing strategies to address it, you can regain your confidence, excel in your role, and enjoy a fulfilling career in the dynamic field of technology. Remember that overcoming imposter syndrome is a journey, and with persistence and self-compassion, you can build the self-assuredness needed to thrive as an IT professional.

Dealing With Imposter Syndrome As An IT Expert


Arsenal fans feeling like they lost the game just indicates how far Arsenal has improved in spite of the in-form Tottenham. With injuries pilling up for them, we hope to see Arteta's technical abilities in the face of very challenging fixtures ahead.


Interesting read.


Football fans were treated to a nail-biting showdown in the 94th North London derby as Arsenal clashed with Tottenham in a thrilling encounter. The match ended in a 2-2 draw, leaving supporters on both sides of the rivalry with plenty to talk about. Let's dive into the details of this action-packed game.

Arsenal Strikes First: The match began with a flurry of excitement, as Arsenal seized the early initiative. Bukayo Saka, a rising star for the Gunners, made his presence felt with a stunning strike that deflected off Tottenham's defender, Romero, before beating the goalkeeper. The Emirates Stadium erupted in jubilation as Arsenal took the lead.

Tottenham's Quick Response: Tottenham, determined not to be outdone, managed to restore parity before the first half break with an impressive goal of their own. The Spurs faithful were relieved to see their team draw level, setting the stage for an intense second half.
![image](https://yakihonne.s3.ap-east-1.amazonaws.com/c07dc7ccd9e3e8649e677845d36e477e6899915f5993829d29311bed552d19a4/files/1695636318627-YAKIHONNES3.jpg)

Romero Again: The second half brought more drama and controversy. Romero, who had earlier been involved in Arsenal's opening goal, found himself at the center of attention once again. This time, it was an unfortunate handball by the Tottenham defender inside the penalty area following a corner kick delivered by none other than Bukayo Saka. Arsenal was awarded a penalty, and Saka coolly stepped up to convert it, putting Arsenal ahead once more.

Jorginho's Blunder and Son's Brace: Just when it seemed Arsenal might clinch victory, fate took an unexpected turn. In a matter of minutes, the momentum swung in Tottenham's favor. A costly blunder by Arsenal substitute Jorginho gifted Tottenham's James Maddison an opportunity he couldn't resist. Maddison capitalized on the mistake and grabbed a second assist to help Son Heung-min claim a brace, much to the delight of the Tottenham faithful.

A Thrilling 2-2 Draw: With the score now level at 2-2, both teams battled fiercely in the closing minutes of the match. The North London derby lived up to its reputation as one of the most exciting fixtures in English football. The final whistle blew, and the match ended in a hard-fought 2-2 draw, leaving fans from both sides with mixed emotions.

The 94th North London derby showcased the passion, intensity, and unpredictability that make football such a beloved sport. Arsenal and Tottenham shared the spoils in a game filled with twists and turns. Bukayo Saka shone brightly for Arsenal, but Tottenham's James Maddison stole the show with his man of the match performance. Both sets of fans will be eagerly anticipating the next instalment of this fierce rivalry.

Thrilling 94th North London Derby Ends in a 2-2 Draw


Introduction
People write to communicate their ideas, knowledge, and thoughts but with different writing platforms now available comes different experiences that could make writing pleasurable or painful especially in this digital age.

In exploring different writing platforms, I came across YakiHonne and it is not like anything I have used before. I came across YakiHonne at a writer's meetup at CoLab hosted by YakiHonne and Co-Hosted by Caleb Peterson, Bello Abdullahi and Olivia Immanuel.

So what is YakiHonne?
YakiHonne is a decentralized writing platform built on Nostr that supports free curation, creation, publishing and reporting of content. You can create an account in a matter of seconds with your public or private keys. For me, I used Alby wallet to create my keys and used it to login.

The Writing Process
To satisfy my curiosity, I went ahead to create my first article to share my experience using the platform. Writing on YakiHonne was just a breeze as there are various tools available presentation, collaboration, publishing, feedback, and community building. The contents can be text, image, and videos.

Publishing and Feedback
After writing the article, publishing can be done with a simple click of a button. With the pool of subscribers, writers can get feedback on their contents. You can even get zaps for your posts.

Community Building
YakiHonne has a community that supports writers and has policies guiding it.

Conclusion
If you are looking for a platform to write on, YakiHonne is definetely your platform of choice.