Python for Data Analysts
48K subscribers
504 photos
64 files
320 links
Find top Python resources from global universities, cool projects, and learning materials for data analytics.

For promotions: @coderfun

Useful links: heylink.me/DataAnalytics
Download Telegram
Pandas Cheatsheet 👆
4
30 Days Python Roadmap for Data Analysts 👆
👍54
Data Visualization with Pandas
4
Greetings from PVR Cloud Tech!! 🌈

🚀 Kickstart Your Career in Azure Data Engineering – The Smart Way in 2025!

📌 Start Date: 30th August 2025

Time: 7 AM – 8 AM IST | Saturday

🔹 Course Content :

https://drive.google.com/file/d/1YufWV0Ru6SyYt-oNf5Mi5H8mmeV_kfP-/view

📱 Join WhatsApp Group:

https://chat.whatsapp.com/JezGFEebk2G3TsZPzTsbZP

📥 Register Now:

https://forms.gle/6cRFoVHJBE6TubZJ7

📺 WhatsApp Channel:

https://www.whatsapp.com/channel/0029Vb60rGU8V0thkpbFFW2n

Cheers.
Team PVR Cloud Tech :)
+91-9346060794
2
Essential Topics to Master Data Science Interviews: 🚀

SQL:
1. Foundations
- Craft SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING
- Embrace Basic JOINS (INNER, LEFT, RIGHT, FULL)
- Navigate through simple databases and tables

2. Intermediate SQL
- Utilize Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
- Embrace Subqueries and nested queries
- Master Common Table Expressions (WITH clause)
- Implement CASE statements for logical queries

3. Advanced SQL
- Explore Advanced JOIN techniques (self-join, non-equi join)
- Dive into Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)
- Optimize queries with indexing
- Execute Data manipulation (INSERT, UPDATE, DELETE)

Python:
1. Python Basics
- Grasp Syntax, variables, and data types
- Command Control structures (if-else, for and while loops)
- Understand Basic data structures (lists, dictionaries, sets, tuples)
- Master Functions, lambda functions, and error handling (try-except)
- Explore Modules and packages

2. Pandas & Numpy
- Create and manipulate DataFrames and Series
- Perfect Indexing, selecting, and filtering data
- Handle missing data (fillna, dropna)
- Aggregate data with groupby, summarizing data
- Merge, join, and concatenate datasets

3. Data Visualization with Python
- Plot with Matplotlib (line plots, bar plots, histograms)
- Visualize with Seaborn (scatter plots, box plots, pair plots)
- Customize plots (sizes, labels, legends, color palettes)
- Introduction to interactive visualizations (e.g., Plotly)

Excel:
1. Excel Essentials
- Conduct Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)
- Dive into charts and basic data visualization
- Sort and filter data, use Conditional formatting

2. Intermediate Excel
- Master Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)
- Leverage PivotTables and PivotCharts for summarizing data
- Utilize data validation tools
- Employ What-if analysis tools (Data Tables, Goal Seek)

3. Advanced Excel
- Harness Array formulas and advanced functions
- Dive into Data Model & Power Pivot
- Explore Advanced Filter, Slicers, and Timelines in Pivot Tables
- Create dynamic charts and interactive dashboards

Power BI:
1. Data Modeling in Power BI
- Import data from various sources
- Establish and manage relationships between datasets
- Grasp Data modeling basics (star schema, snowflake schema)

2. Data Transformation in Power BI
- Use Power Query for data cleaning and transformation
- Apply advanced data shaping techniques
- Create Calculated columns and measures using DAX

3. Data Visualization and Reporting in Power BI
- Craft interactive reports and dashboards
- Utilize Visualizations (bar, line, pie charts, maps)
- Publish and share reports, schedule data refreshes

Statistics Fundamentals:
- Mean, Median, Mode
- Standard Deviation, Variance
- Probability Distributions, Hypothesis Testing
- P-values, Confidence Intervals
- Correlation, Simple Linear Regression
- Normal Distribution, Binomial Distribution, Poisson Distribution.

Show some ❤️ if you're ready to elevate your data science journey! 📊

ENJOY LEARNING 👍👍
7