Python Pandas Question and Answer Video Series

Python pandas Q&A video series

Read about the series, and view all of the videos on one page: Easier data analysis in Python with pandas.

Jupyter Notebooks

• Python pandas Q&A series (videos 1 to 30)
• How do I use the MultiIndex in pandas? (video 31)
• How do I merge DataFrames in pandas? (video 32)
• 4 new time-saving tricks in pandas (video 33)
• 5 new changes in pandas you need to know about (video 34)
• My top 25 pandas tricks (video 35)
• Data Science Best Practices with pandas (PyCon 2019) (video 36)

Videos (playlist)

1. What is pandas? (Introduction to the Q&A series) (6:24)
2. How do I read a tabular data file into pandas? (8:54)
3. How do I select a pandas Series from a DataFrame? (11:10)
4. Why do some pandas commands end with parentheses (and others don't)? (8:45)
5. How do I rename columns in a pandas DataFrame? (9:36)
6. How do I remove columns from a pandas DataFrame? (6:35)
7. How do I sort a pandas DataFrame or a Series? (8:56)
8. How do I filter rows of a pandas DataFrame by column value? (13:44)
9. How do I apply multiple filter criteria to a pandas DataFrame? (9:51)
10. Your pandas questions answered! (9:06)
11. How do I use the "axis" parameter in pandas? (8:33)
12. How do I use string methods in pandas? (6:16)
13. How do I change the data type of a pandas Series? (7:28)
14. When should I use a "groupby" in pandas? (8:24)
15. How do I explore a pandas Series? (9:50)
16. How do I handle missing values in pandas? (14:27)
17. What do I need to know about the pandas index? (Part 1) (13:36)
18. What do I need to know about the pandas index? (Part 2) (10:38)
19. How do I select multiple rows and columns from a pandas DataFrame? (21:46)
20. When should I use the "inplace" parameter in pandas? (10:18)
21. How do I make my pandas DataFrame smaller and faster? (19:05)
22. How do I use pandas with scikit-learn to create Kaggle submissions? (13:25)
23. More of your pandas questions answered! (19:23)
24. How do I create dummy variables in pandas? (13:13)
25. How do I work with dates and times in pandas? (10:20)
26. How do I find and remove duplicate rows in pandas? (9:47)
27. How do I avoid a SettingWithCopyWarning in pandas? (13:29)
28. How do I change display options in pandas? (14:55)
29. How do I create a pandas DataFrame from another object? (14:25)
30. How do I apply a function to a pandas Series or DataFrame? (17:57)
31. Bonus: How do I use the MultiIndex in pandas? (25:00)
32. Bonus: How do I merge DataFrames in pandas? (21:48)
33. Bonus: 4 new time-saving tricks in pandas (14:50)
34. Bonus: 5 new changes in pandas you need to know about (20:54)
35. Bonus: My top 25 pandas tricks (27:37)
36. Bonus: Data Science Best Practices with pandas (PyCon 2019) (1:44:16)
37. Bonus: Your pandas questions answered! (webcast) (1:56:01)

Datasets

Filename	Description	Raw File	Original Source	Other
chipotle.tsv	Online orders from the Chipotle restaurant chain	bit.ly/chiporders	The Upshot	Upshot article
drinks.csv	Alcohol consumption by country	bit.ly/drinksbycountry	FiveThirtyEight	FiveThirtyEight article
imdb_1000.csv	Top rated movies from IMDb	bit.ly/imdbratings	IMDb	Web scraping script
stocks.csv	Small dataset of stock prices	bit.ly/smallstocks	DataCamp
titanic_test.csv	Testing set from Kaggle's Titanic competition	bit.ly/kaggletest	Kaggle	Data dictionary
titanic_train.csv	Training set from Kaggle's Titanic competition	bit.ly/kaggletrain	Kaggle	Data dictionary
u.data	Movie ratings by MovieLens users	bit.ly/movielensdata	GroupLens	Data dictionary
u.item	Movie information from MovieLens	bit.ly/movieitems	GroupLens	Data dictionary
u.user	Demographic information about MovieLens users	bit.ly/movieusers	GroupLens	Data dictionary
ufo.csv	Reports of UFO sightings from 1930-2000	bit.ly/uforeports	National UFO Reporting Center	Web scraping script

Download Details:
Author: justmarkham
Source Code: https://github.com/justmarkham/pandas-videos
License: 

#pandas  #python #jupyter #data-analysis 

What is GEEK

Buddha Community

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Python Pandas Objects - Pandas Series and Pandas Dataframe

In this post, we will learn about pandas’ data structures/objects. Pandas provide two type of data structures:-

Pandas Series

Pandas Series is a one dimensional indexed data, which can hold datatypes like integer, string, boolean, float, python object etc. A Pandas Series can hold only one data type at a time. The axis label of the data is called the index of the series. The labels need not to be unique but must be a hashable type. The index of the series can be integer, string and even time-series data. In general, Pandas Series is nothing but a column of an excel sheet with row index being the index of the series.

Pandas Dataframe

Pandas dataframe is a primary data structure of pandas. Pandas dataframe is a two-dimensional size mutable array with both flexible row indices and flexible column names. In general, it is just like an excel sheet or SQL table. It can also be seen as a python’s dict-like container for series objects.

#python #python-pandas #pandas-dataframe #pandas-series #pandas-tutorial

50 Python Interview Questions and Answers

Ace your next coding interview

Are you preparing for a job interview or an exam that involves knowledge about Python? Or do you want to quickly go through common topics of Python?

Here is a list of 50 interview questions with answers. The list is in no particular order.

I hope you enjoy it.

1. Name Some Differences Between a List and a Tuple

2. What Does the Range() Function Do?

3. How Does Map() Function Work?

4. What is the Difference between “is” and “==”?

…

#python #data-science #software-development #50 python interview questions and answers #interview questions and answers #python interview questions and answers

Pandas in Python

Pandas is used for data manipulation, analysis and cleaning.

What are Data Frames and Series?

Dataframe is a two dimensional, size mutable, potentially heterogeneous tabular data.

It contains rows and columns, arithmetic operations can be applied on both rows and columns.

Series is a one dimensional label array capable of holding data of any type. It can be integer, float, string, python objects etc. Panda series is nothing but a column in an excel sheet.

How to create dataframe and series?

s = pd.Series([1,2,3,4,56,np.nan,7,8,90])

print(s)

How to create a dataframe by passing a numpy array?

1. d= pd.date_range(‘20200809’,periods=15)
2. print(d)
3. df = pd.DataFrame(np.random.randn(15,4), index= d, columns = [‘A’,’B’,’C’,’D’])
4. print(df)

#pandas-series #pandas #pandas-in-python #pandas-dataframe #python

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development