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I teach below topics for Data Science Course. The online tutoring via skype desktop sharing is only 40 USD per hour. For booking a class send message or call my whatsapp number: +98 912 490 8372


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Complete Course of Data Science with Pandas Library

Lesson

Lesson Subject

pdf file

1

Introduction to Data Science

Lesson 1

2

Introduction to Pandas in Python

Lesson 2

3

How to Install Python Pandas on Windows and Linux?

Lesson 3

4

How To Use Jupyter Notebook: An Ultimate Guide

Lesson 4

5

Python --> Pandas DataFrame

Lesson 5

6

Creating a Pandas DataFrame

Lesson 6

7

Python --> Pandas Series

Lesson 7

8

Creating a Pandas Series

Lesson 8

9

View the top rows of the frame

Lesson 9

10

View the bottom rows of the frame

Lesson 10

11

View basic statistical details

Lesson 11

12

Convert the pandas DataFrame to numpy Array

Lesson 12

13

Convert the pandas Series to numpy Array

Lesson 13

14

Convert series or dataframe object to Numpy-array using .as_matrix()

Lesson 14

15

Dealing with Rows and Columns in Pandas DataFrame

Lesson 15

16

How to select multiple columns in a pandas dataframe

Lesson 16

17

Python --> Pandas Extracting rows using .loc[]

Lesson 17

18

Python --> Extracting rows using Pandas .iloc[]

Lesson 18

19

Indexing and Selecting Data with Pandas

Lesson 19

20

Boolean Indexing in Pandas

Lesson 20

21

Label and Integer based slicing technique using DataFrame.ix[]

Lesson 21

22

Adding new column to existing DataFrame in Pandas

Lesson 22

23

Python --> Delete rows/columns from DataFrame

Lesson 23

24

Truncate a DataFrame before and after some index value

Lesson 24

25

Truncate a Series before and after some index value

Lesson 25

26

Iterating over rows and columns in Pandas DataFrame

Lesson 26

27

Working with Missing Data in Pandas

Lesson 27

28

Sorts a data frame in Pandas --> Set-1

Lesson 28

29

Sorts a data frame in Pandas --> Set-2

Lesson 29

30

Pandas GroupBy

Lesson 30

31

Grouping Rows in pandas

Lesson 31

32

Combining multiple columns in Pandas groupby with dictionary

Lesson 32

33

Python --> Pandas Merging, Joining, and Concatenating

Lesson 33

34

Concatenate Strings

Lesson 34

35

Append rows to Dataframe

Lesson 35

36

Concatenate two or more series

Lesson 36

37

Append a single or a collection of indices

Lesson 37

38

Combine two series into one

Lesson 38

39

Add a row at top in pandas DataFrame

Lesson 39

40

Join all elements in list present in a series

Lesson 40

41

Join two text columns into a single column in Pandas

Lesson 41

42

Python --> Working with date and time using Pandas

Lesson 42

43

Timestamp using Pandas

Lesson 43

44

Current Time using Pandas

Lesson 44

45

Convert timestamp to ISO Format

Lesson 45

46

Get datetime object using Pandas

Lesson 46

47

Replace the member values of the given Timestamp

Lesson 47

48

Convert string Date time into Python Date time object using Pandas

Lesson 48

49

Get a fixed frequency DatetimeIndex using Pandas

Lesson 49

50

Python --> Pandas Working With Text Data

Lesson 50

51

Convert String into lower, upper or camel case

Lesson 51

52

Replace Text Value

Lesson 52

53

Replace Text Value using series.replace()

Lesson 53

54

Removing Whitespaces

Lesson 54

55

Move dates forward a given number of valid dates using Pandas

Lesson 55

56

Read csv using pandas

Lesson 56

57

Saving a Pandas Dataframe as a CSV

Lesson 57

58

Loading Excel spreadsheet as pandas DataFrame

Lesson 58

59

Creating a dataframe using Excel files

Lesson 59

60

Working with Pandas and XlsxWriter --> Set – 1

Lesson 60

61

Working with Pandas and XlsxWriter --> Set – 2

Lesson 61

62

Working with Pandas and XlsxWriter --> Set – 3

Lesson 62

63

Apply a function on the possible series

Lesson 63

64

Apply function to every row in a Pandas DataFrame

Lesson 64

65

Apply a function on each element of the series

Lesson 65

66

Aggregation data across one or more column

Lesson 66

67

Mean of the values for the requested axis

Lesson 67

68

Mean of the underlying data in the Series

Lesson 68

69

Mean absolute deviation of the values for the requested axis

Lesson 69

70

Mean absolute deviation of the values for the Series

Lesson 70

71

Unbiased standard error of the mean

Lesson 71

72

Find the Series containing counts of unique values

Lesson 72

73

Find the Series containing counts of unique values using Index.value_counts()

Lesson 73

74

Pandas Built-in Data Visualization

Lesson 74

75

Data analysis and Visualization with Python --> Set 1

Lesson 75

76

Data analysis and Visualization with Python --> Set 2

Lesson 76

77

Box plot visualization with Pandas and Seaborn

Lesson 77

78

How to Do a vLookup in Python using pandas

Lesson 78

79

Convert CSV to HTML Table in Python

Lesson 79

80

KDE Plot Visualization with Pandas and Seaborn

Lesson 80

81

Analyzing selling price of used cars using Python

Lesson 81

82

Add CSS to the Jupyter Notebook using Pandas

Lesson 82

Stimated Required time for this course is: 90 hour


Data Science Development
Data Science with Python
Data Science Logo
Data Science Developer
Data Science Tutorial
Data Science Tutor
Data Science Online Tutor
Data Science Video Lecture
Data Science Free Tutorial
Data Science with Pandas
Data Science Best Practices

Hint: The online tutoring via skype desktop sharing is only 40 USD per hour. For booking a class send message or call my whatsapp number: +98 912 490 8372


Data Science Development
Data Science with Python
Data Science Logo
Data Science Developer
Data Science Tutorial
Data Science Tutor
Data Science Online Tutor
Data Science Video Lecture
Data Science Free Tutorial
Data Science with Pandas
Data Science Best Practices





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