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@juannovoa._: Chururu sin electricidad 🕯 #Venezuela #🇻🇪 #DerechosHumanos #electricidad #tachira

Juan Novoa
Juan Novoa
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Region: VE
Tuesday 06 October 2026 21:37:41 GMT
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Comments

dayanakeyla2409
Dayana :
ustedes llevan 3 días y por donde vivo tenemos 8 días sin luz 😳
2026-10-07 01:03:39
11
andencsonjovannyj
jaimes :
el Táchira se está activandoooo
2026-10-07 01:26:02
13
noemy.ramon.leal
Noemy Ramon Leal :
vamos Táchira hasta cuándo esté peo
2026-10-06 22:58:24
8
renzy63gil
renzy63gil :
ni ellos saben dar la solución, están en una encrucijada ya que la solución es reemplazar la chatarra por nuevos equipos actualizados. inversión que nunca hicieron
2026-10-06 22:40:06
6
jorgearias1963
Jorge S. Arias V :
2026-10-07 00:29:28
0
lagocha481
❤️La flaca❤️ :
vamos mañana gente en la lucha
2026-10-07 01:11:53
0
nubel1959
𝖭𝗎𝖻el :
hoy la quitaron a las 11 am llego a las 4pm se fue a las 6pm ahora esperar a q hora llega
2026-10-06 23:19:59
0
henrylaureanomene
Marii 🌼 :
eso hace falta aquí en rubio que la gente salga aquí sin luz sin gas esto está feo
2026-10-07 00:04:57
0
clara.linda.2504
💟🇻🇪Clara linda 2504🇻🇪 :
así es
2026-10-07 01:38:04
0
yamira.caro
Yamira Caro :
2026-10-06 22:43:58
0
jorgearias1963
Jorge S. Arias V :
2026-10-07 00:29:31
0
zenaida.ramrez.he
Zenaida Ramírez Hernández :
2026-10-06 23:01:35
0
darwincuadros35
Darwincuadros35 :
👍👍👍
2026-10-07 11:29:46
0
osnorvitsanchez
osnorvit Sanchez :
👍
2026-10-06 23:35:09
0
alberto.buitrago4
Alberto Buitrago :
[Me gusta][Me gusta][Me gusta]
2026-10-06 22:07:14
0
lucy.ascanio2
Lucy Ascanio :
🙏💯👍👍💯🇻🇪👍
2026-10-07 12:34:18
0
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Choosing the right plot is just as important as creating the plot. The goal isn’t to make charts look pretty. The goal is to make patterns easy to understand. 🧠 1️⃣ LINE PLOT 📈 Use when: Showing trends over time. Examples: → Sales over months → Stock prices → Website traffic Question: How is it changing? 2️⃣ BAR PLOT 📊 Use when: Comparing categories. Examples: → Sales by product → Revenue by department → Students by grade Question: Which is bigger? 3️⃣ HISTOGRAM 📉 Use when: Understanding the distribution of numerical data. Examples: → Age distribution → Salary distribution → Exam scores Question: How are the values distributed? 4️⃣ SCATTER PLOT 🔵 Use when: Studying the relationship between two numerical variables. Examples: → Experience vs Salary → Height vs Weight → Advertising Spend vs Sales Question: Are these variables related? 5️⃣ BOX PLOT 📦 Use when: Understanding spread and detecting outliers. Shows: → Median → Quartiles → Range → Potential outliers Question: How spread out is the data? 6️⃣ COUNT PLOT 🔢 Use when: Counting observations in each category. Examples: → Customers by gender → Orders by category → Number of passengers by class Question: How many are in each category? 7️⃣ PIE / DONUT CHART 🥧 Use when: Showing simple part-to-whole proportions. Examples: → Market share → Budget allocation → Customer segments Question: What percentage does each category represent? ⚠️ Avoid using pie charts when there are many categories. 8️⃣ HEATMAP 🔥 Use when: Visualizing matrices, correlations, or intensity. Examples: → Correlation matrix → Website activity → Missing-value patterns Question: Where are the strongest patterns? 9️⃣ VIOLIN PLOT 🎻 Use when: Comparing distributions across categories. It combines ideas from: Box Plot + Distribution Density Question: How does the distribution differ between groups? 🔟 PAIR PLOT 🔗 Use when: Exploring relationships among multiple numerical variables. Useful during EDA. Question: How do multiple features relate to each other? 🧠 QUICK MEMORY GUIDE Trend → Line Plot 📈 Comparison → Bar Plot 📊 Distribution → Histogram 📉 Relationship → Scatter Plot 🔵 Outliers → Box Plot 📦 Counts → Count Plot 🔢 Part-to-whole → Pie Chart 🥧 Correlation → Heatmap 🔥 Multiple distributions → Violin Plot 🎻 Multiple features → Pair Plot 🔗 🚀 DATA VISUALIZATION WORKFLOW Raw Data ↓ Clean Data ↓ EDA ↓ Choose the Right Plot ↓ Find Patterns ↓ Generate Insights ↓ Tell the Story 💡 Remember: A beautiful visualization with the wrong plot can still communicate the wrong message. Good analysts don’t just create charts. They know which chart answers the question. 🎯 📌 Save this as your Data Visualization cheat sheet. #DataVisualization #DataScience #DataAnalysis #EDA #creatorsearchinsights
Choosing the right plot is just as important as creating the plot. The goal isn’t to make charts look pretty. The goal is to make patterns easy to understand. 🧠 1️⃣ LINE PLOT 📈 Use when: Showing trends over time. Examples: → Sales over months → Stock prices → Website traffic Question: How is it changing? 2️⃣ BAR PLOT 📊 Use when: Comparing categories. Examples: → Sales by product → Revenue by department → Students by grade Question: Which is bigger? 3️⃣ HISTOGRAM 📉 Use when: Understanding the distribution of numerical data. Examples: → Age distribution → Salary distribution → Exam scores Question: How are the values distributed? 4️⃣ SCATTER PLOT 🔵 Use when: Studying the relationship between two numerical variables. Examples: → Experience vs Salary → Height vs Weight → Advertising Spend vs Sales Question: Are these variables related? 5️⃣ BOX PLOT 📦 Use when: Understanding spread and detecting outliers. Shows: → Median → Quartiles → Range → Potential outliers Question: How spread out is the data? 6️⃣ COUNT PLOT 🔢 Use when: Counting observations in each category. Examples: → Customers by gender → Orders by category → Number of passengers by class Question: How many are in each category? 7️⃣ PIE / DONUT CHART 🥧 Use when: Showing simple part-to-whole proportions. Examples: → Market share → Budget allocation → Customer segments Question: What percentage does each category represent? ⚠️ Avoid using pie charts when there are many categories. 8️⃣ HEATMAP 🔥 Use when: Visualizing matrices, correlations, or intensity. Examples: → Correlation matrix → Website activity → Missing-value patterns Question: Where are the strongest patterns? 9️⃣ VIOLIN PLOT 🎻 Use when: Comparing distributions across categories. It combines ideas from: Box Plot + Distribution Density Question: How does the distribution differ between groups? 🔟 PAIR PLOT 🔗 Use when: Exploring relationships among multiple numerical variables. Useful during EDA. Question: How do multiple features relate to each other? 🧠 QUICK MEMORY GUIDE Trend → Line Plot 📈 Comparison → Bar Plot 📊 Distribution → Histogram 📉 Relationship → Scatter Plot 🔵 Outliers → Box Plot 📦 Counts → Count Plot 🔢 Part-to-whole → Pie Chart 🥧 Correlation → Heatmap 🔥 Multiple distributions → Violin Plot 🎻 Multiple features → Pair Plot 🔗 🚀 DATA VISUALIZATION WORKFLOW Raw Data ↓ Clean Data ↓ EDA ↓ Choose the Right Plot ↓ Find Patterns ↓ Generate Insights ↓ Tell the Story 💡 Remember: A beautiful visualization with the wrong plot can still communicate the wrong message. Good analysts don’t just create charts. They know which chart answers the question. 🎯 📌 Save this as your Data Visualization cheat sheet. #DataVisualization #DataScience #DataAnalysis #EDA #creatorsearchinsights
ইশ্বর কি তোমার আমার, মিলন লিখতে পারতো না ❤️‍🩹 . . . . . . . #mdemon440 #vairal #bdtiktokofficial🇧🇩 @TikTok @For You @TikTok Bangladesh
ইশ্বর কি তোমার আমার, মিলন লিখতে পারতো না ❤️‍🩹 . . . . . . . #mdemon440 #vairal #bdtiktokofficial🇧🇩 @TikTok @For You @TikTok Bangladesh

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