Python Pioneers: A Beginner's Guide 🇪🇹 – Telegram
Python Pioneers: A Beginner's Guide 🇪🇹
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Welcome to Python Pioneers: Empowering Ethiopian students to embark on their coding journey. 🚀🌐🗺📱🖥💻🖱🛰

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We just hit 4,000 subscribers! 🚀 Your support, engagement, and love keep this community growing every day. Thank you for being part of this journey!

Let's keep learning, sharing, and inspiring together. More exciting content is on the way!

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Next: Data Visualization in Python

በቀጣይ አንድን መረጃ Pythonን በመጠቀም እንዴት visualize ማረግ እንደምንችል እናያለን።

Stay Tuned!

#DataVisualizationInPython

@python_pioneers
📊 Understanding Data Visualization in Python

🔹Data Visualization ምንድነው?

Data visualization የምንለው አንድን መረጃ graphically ወይም በሚታይ መልኩ የምናስቀምጥበት ወይም represent የምናረግበት ሂደት ነው።

በData Processing stages ውስጥ Data visualizationን የሚገባው በ Data Output ውይም Data interpretation እና Analysis ደረጃ ላይ ነው።

Data Output stage ላይ እንደ እነ charts, graphs, የመሳሰሉት የvisualization tools processed መረጃን ለመረዳት በሚቀል መልኩ እንድናስቀምጥ ይረዱናል።

Data Interpretation እና Analysis stage ላይ visualization የ አንድን መረጃ pattern ወይም trend እንድንረዳ፡ እናም መረጃ ላይ የተመሠረተ ውሳኔ እንድንወስን ያግዘናል።


Good data visualization enhances understanding and communication, making complex data more accessible.


To be cont'd

#DataVisualization
#Data

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በPython, data visualization moduleኦች በእነዚህ ቁልፍ ደረጃዎች ይሰራሉ።


1. Import the required library – Common libraries include matplotlib, seaborn, and plotly.

import matplotlib.pyplot as plt
import seaborn as sns


2. Prepare the data – Load or create a dataset.

data = [10, 20, 15, 25, 30]

3. Create the plot – Use functions to generate a visualization.

plt.plot(data)

4. Customize the visualization – Add labels, noscripts, colors, or styles.

plt.noscript("Simple Line Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")

5. Display the visualization – Render the plot.

plt.show()


This process applies to various chart types like bar plots, histograms, and scatter plots, depending on the library and data used.

to be cont'd

#DataVisualization
#Data

@python_pioneers
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በPython, data visualization moduleኦች በእነዚህ ቁልፍ ደረጃዎች ይሰራሉ።


1. Import the required library – Common libraries include matplotlib, seaborn, and plotly.

import matplotlib.pyplot as plt
import seaborn as sns

2. Prepare the data – Load or create a dataset.

data = [10, 20, 15, 25, 30]

3. Create the plot – Use functions to generate a visualization.

plt.plot(data)

4. Customize the visualization – Add labels, noscripts, colors, or styles.

plt.noscript("Simple Line Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")

5. Display the visualization – Render the plot.

plt.show()



This process applies to various chart types like bar plots, histograms, and scatter plots, depending on the library and data used.


#DataVisualization
#Data

@python_pioneers
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🔥, 3

#Quizzes

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Forwarded from Dagmawi Babi
This is for everyone that is looking to start or progress through their programming journey!

If you are looking to start your programming journey, or have started it but don't have a clear goal or path on where and how you should move forward; I have compiled and made a really simple and straight forward path for you!

No, you don't need a mentor. You just need a computer and access to internet, that's all.

I have posted all the guides, resources and advices all in my community. Now you don't have to go around asking every dev or community to be your mentor or to give you a roadmap or something. This'll help exponentially.

Ofcourse my advices and plan will not fit all of you. You just have to use and apply the ones that apply to your scenario and go from there.

Here are the roadmaps and resources
https://news.1rj.ru/str/dagmawibabichat/37512/54629

Share it with your friends and community, for people who want to get into programming and for people who want to progress.

I hope it helps. 🌷

#Resources #Roadmap #Programming
@Dagmawi_Babi
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