Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources
Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun
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Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources (@learndataanalysis) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 53 308 obunachidan iborat bo'lib, Taʼlim toifasida 3 300-o'rinni va Hindiston mintaqasida 6 450-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 53 308 obunachiga ega bo‘ldi.
30 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 60 ga, so‘nggi 24 soatda esa 5 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 7.05% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.16% ini tashkil etuvchi reaksiyalarni to‘playdi.
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- Tematik yo‘nalishlar: Kontent analyst, |--, excel, visualization, analytic kabi asosiy mavzularga jamlangan.
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Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Data Analysis Useful Resources
#dataanalysis
#dataanalysisbooks
#sqlbooks
#pythonbooks
#tableau
#powerbi
#datavisualization
For promotions: @coderfun”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 31 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
CREATE TABLE numeric_example (
id INT,
amount DECIMAL(10, 2)
);
1. String Data Types:
- CHAR, VARCHAR: For fixed and variable-length strings.
- TEXT: For large text.
- BLOB: For binary large objects like images.
- Example:
CREATE TABLE string_example (
name VARCHAR(100),
description TEXT
);
1. Date and Time Data Types:
- DATE, DATETIME, TIMESTAMP: For date and time values.
- YEAR: For storing a year.
- Example:
CREATE TABLE datetime_example (
created_at DATETIME,
year_of_joining YEAR
);
Interview Questions:
- Q1: What is the difference between CHAR and VARCHAR?
A1: CHAR has a fixed length, while VARCHAR has a variable length. VARCHAR is more storage-efficient for varying-length data.
- Q2: When should you use DECIMAL instead of FLOAT?
A2: Use DECIMAL for precise calculations (e.g., financial data) and FLOAT for approximate values where precision is less critical.