Data Science Tutorial Contents

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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

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

Why Do I Need a Tutor?! Click here to know

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

Complete Course of Data Science with Pandas Library

Lesson

Lesson Subject

pdf file

1

Introduction to Data Science

2

Introduction to Pandas in Python

3

How to Install Python Pandas on Windows and Linux?

4

How To Use Jupyter Notebook: An Ultimate Guide

5

Python → Pandas DataFrame

6

Creating a Pandas DataFrame

7

Python → Pandas Series

8

Creating a Pandas Series

9

View the top rows of the frame

10

View the bottom rows of the frame

11

View basic statistical details

12

Convert the pandas DataFrame to numpy Array

13

Convert the pandas Series to numpy Array

14

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

15

Dealing with Rows and Columns in Pandas DataFrame

16

How to select multiple columns in a pandas dataframe

17

Python → Pandas Extracting rows using .loc[]

18

Python → Extracting rows using Pandas .iloc[]

19

Indexing and Selecting Data with Pandas

20

Boolean Indexing in Pandas

21

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

22

Adding new column to existing DataFrame in Pandas

23

Python → Delete rows/columns from DataFrame

24

Truncate a DataFrame before and after some index value

25

Truncate a Series before and after some index value

26

Iterating over rows and columns in Pandas DataFrame

27

Working with Missing Data in Pandas

28

Sorts a data frame in Pandas → Set-1

29

Sorts a data frame in Pandas → Set-2

30

Pandas GroupBy

31

Grouping Rows in pandas

32

Combining multiple columns in Pandas groupby with dictionary

33

Python → Pandas Merging, Joining, and Concatenating

34

Concatenate Strings

35

Append rows to Dataframe

36

Concatenate two or more series

37

Append a single or a collection of indices

Why Do I Need a Tutor?!
Click here to know