Your skills are like a supercar.......don't let them rust in the wrong environment. Seek challenges that push you to your limits.
#Quote
#PushYourLimits
@python_pioneers
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🎉 4000 Strong! 🎉
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!
#RoadTo5K
#ThankYou
#CommunityStrong
@python_pioneers
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!
#RoadTo5K
#ThankYou
#CommunityStrong
@python_pioneers
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Next: Data Visualization in Python
በቀጣይ አንድን መረጃ Pythonን በመጠቀም እንዴት visualize ማረግ እንደምንችል እናያለን።
Stay Tuned!
#DataVisualizationInPython
@python_pioneers
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።
To be cont'd
#DataVisualization
#Data
@python_pioneers
🔹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
@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.
2. Prepare the data – Load or create a dataset.
3. Create the plot – Use functions to generate a visualization.
4. Customize the visualization – Add labels, noscripts, colors, or styles.
5. Display the visualization – Render the plot.
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
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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♟️ Chess Facts You Should Know! ♟️
🔹 There are 400 possible positions after each player's first move. After two moves, this number jumps to 72,084!
🔹 The longest possible game is 5,949 moves without a draw by the 50-move rule.
🔹 The "en passant" rule allows a pawn to capture an opponent's pawn that has just moved two squares forward.
🔹 The fastest checkmate is called Fool’s Mate and happens in just 2 moves: 1. f3 e5 2. g4 Qh4#.
🔹 A pawn can promote to a queen, rook, bishop, or knight when reaching the 8th rank—choosing a knight can deliver a surprise check!
#Chess
@python_pioneers
🔹 There are 400 possible positions after each player's first move. After two moves, this number jumps to 72,084!
🔹 The longest possible game is 5,949 moves without a draw by the 50-move rule.
🔹 The "en passant" rule allows a pawn to capture an opponent's pawn that has just moved two squares forward.
🔹 The fastest checkmate is called Fool’s Mate and happens in just 2 moves: 1. f3 e5 2. g4 Qh4#.
🔹 A pawn can promote to a queen, rook, bishop, or knight when reaching the 8th rank—choosing a knight can deliver a surprise check!
#Chess
@python_pioneers
👍1
በPython, data visualization moduleኦች በእነዚህ ቁልፍ ደረጃዎች ይሰራሉ።
1. Import the required library – Common libraries include matplotlib, seaborn, and plotly.
2. Prepare the data – Load or create a dataset.
3. Create the plot – Use functions to generate a visualization.
4. Customize the visualization – Add labels, noscripts, colors, or styles.
5. Display the visualization – Render the plot.
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
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
💯1