Curiasity | Data analysis in Python

Course / Course Details

Data analysis in Python

Programming

By - Sasikala
0 students
N/A
(0)

Course Description

This course introduces learners to data analysis using Python, one of the most powerful programming languages for handling and interpreting data. Students will learn how to collect, clean, process, analyze, and visualize data using popular Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn. The course covers real-world data analysis techniques, statistical concepts, and practical projects to help learners build confidence in solving data-driven problems.

Course Outcomes

By the end of this course, learners will be able to:

Understand the fundamentals of Python programming for data analysis.
Import, clean, and manipulate datasets efficiently.
Perform data analysis using Pandas and NumPy.
Create meaningful charts and visualizations using Matplotlib and Seaborn.
Apply statistical techniques to interpret data trends and patterns.
Work with CSV, Excel, and other structured data formats.
Build data-driven reports and dashboards.
Complete practical projects using real-world datasets.
Improve problem-solving skills using analytical thinking.
Prepare for advanced topics like machine learning and big data analytics.

Course Curriculum

1 chapters
38 lectures
0 quizzes
N/A total length

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1 What is pandas Introduction to the Q A series

6.25 Min

2 How do I read a tabular data file into pandas

8.54 Min

3 How do I select a pandas Series from a DataFrame

11.11 Min

4 Why do some pandas commands end with parentheses and others don t

8.45 Min

5 How do I rename columns in a pandas DataFrame

9.36 Min

6 How do I remove columns from a pandas DataFrame

6.35 Min

7 How do I sort a pandas DataFrame or a Series

8.56 Min

8 How do I filter rows of a pandas DataFrame by column value

13.45 Min

9 How do I apply multiple filter criteria to a pandas DataFrame

9.51 Min

10 Your pandas questions answered

9.06 Min

11 How do I use the axis parameter in pandas

8.33 Min

12 How do I use string methods in pandas

6.17 Min

13 How do I change the data type of a pandas Series

7.28 Min

14 When should I use a groupby in pandas

8.24 Min

15 How do I explore a pandas Series

9.5 Min

16 How do I handle missing values in pandas

14.27 Min

17 What do I need to know about the pandas index Part 1

13.36 Min

18 What do I need to know about the pandas index Part 2

10.38 Min

19 How do I select multiple rows and columns from a pandas DataFrame

21.46 Min

20 When should I use the inplace parameter in pandas

10.18 Min

21 How do I make my pandas DataFrame smaller and faster

19.05 Min

22 How do I use pandas with scikit learn to create Kaggle submissions

13.25 Min

23 More of your pandas questions answered

19.23 Min

24 How do I create dummy variables in pandas

13.13 Min

25 How do I work with dates and times in pandas

10.21 Min

26 How do I find and remove duplicate rows in pandas

9.47 Min

27 How do I avoid a SettingWithCopyWarning in pandas

13.3 Min

28 How do I change display options in pandas

14.55 Min

29 How do I create a pandas DataFrame from another object

14.25 Min

30 How do I apply a function to a pandas Series or DataFrame

17.57 Min

31 How do I use the MultiIndex in pandas

25.01 Min

32 How do I merge DataFrames in pandas

21.49 Min

33 4 new time saving tricks in pandas

14.5 Min

34 5 new changes in pandas you need to know about

20.54 Min

35 My top 25 pandas tricks

27.38 Min

36 21 more pandas tricks

24.39 Min

37 Data Science Best Practices with pandas PyCon 2019

1 Hour 44.16 Min

38 Your pandas questions answered webcast

1 Hour 56.01 Min

Instructor

Sasikala

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Duration N/A
Lectures 38 lessons
Enrolled 0 students
Category: Programming
0 Quizzes
Language: English
Skill Level Beginner
Certificate of Completion
Full lifetime access

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