Dplyr::groupby(iris, Species) Group data into rows with the same value of Species. Dplyr::ungroup(iris) Remove grouping information from data frame. Importing Data: Python Cheat Sheet. January 11th, 2018 A cheat sheet that covers several ways of getting data into Python: from flat files such as.txts and.csv to files native to other software, such as Excel, SAS, or Matlab, and relational databases such as SQLite & PostgreSQL.
Hey Finxters! I have another set of cheat sheets for you! This time, I am going to focus on the more advanced aspects of Python and what you can do with it! As you know Python is a flexible language used in web development, games, and desktop applications. I am not going to waste too much of your time so let’s hop right to it and dive into these more advanced Python cheat sheets!
Cheat Sheet 0: Finxter Full Cheat Sheet Course
Cheat Sheet 1: DataQuest
This cheat sheet is from DataQuest and it shows all of the intermediate Python
Regular expressions, date/time module, and counter. This is one you will want to have pinned to the wall or in your developers binder to keep handy as you work. American truck simulator - valentines paint jobs pack download free.
Pros: Great for budding Python developers, keep it handy as you work.
Cons: Car mechanic simulator 2015 - bentley download. None that I can see.
Cheat Sheet 2: DataCamp
It is important to know how to import data during your career no matter what stage you are at. As an intermediate Pythoner, you should keep this cheat sheet handy when working an entry level job of data entry and developing you own projects.
Pros: Great for learning importing data sets in Python.
Cons: None that I can see.
Cheat Sheet 3: DataCamp
You have to import data and you have to be able to plot it as a visual representation for businesses to understand and use to their benefit. This cheat sheet will help you to learn matplotlib and write some amazing graphical visualizations with Python.
Pros: Great to have for matplotlib development.
Cons: None that I can see.
Cheat Sheet 4: GitHub
This cheat sheet is for Machine learning and one you will want to keep in your developers binder as you work. Machine learning and Python go together like peanut butter and jelly, and Scikit is going to be your best friend. If your developers journey takes you to machine learning then make sure to keep this cheat handy for yourself.
Pros: Scikit is easily learnable with this cheat sheet
Cons: None that I can see.
Cheat Sheet 5: DataCamp
SQL is a database system used in programming for all kinds of data sets and is extremely scalable. Keep this cheat sheet handy to you! BI and other business applications rely on you being able to use SQL!
Pros: Rated ‘E’ for everyone. Easy to read and implement
Cons: None that I can see.
Cheat Sheet 6: Pytorch
This cheat sheet is more a tutorial that will teach you pytorch for deep learning projects. Here you will get hands on practice on pytorch.
Pros: You will get a deep understanding pytorch and how it used
Cons: It is an online tutorial.
Cheat Sheet 7: DataCamp
Yet another from Datacamp!! This one is called SpaCy and allows you to understand the natural text from documents. This is one I have in my development folder and is used for Natural language programming.
Pros: Rated ‘E’ for everyone.
Cons: None that I can see.
Cheat Sheet 8: Ask Python
This cheat sheet is also more a tutorial for you to learn image processing in Python. The best way to learn is to get your hands dirty! Ask Python is good for doing that so you can learn what you need to and boost your skills.
Pros: Rated ‘E’ for everyone.
Cons: None that I can see.
Cheat Sheet 9: TutorialsPoint
This cheat sheet is also a tutorial on learning database access with Python. This is an incredibly important skill when you freelance your skills or end up working for a company at a data entry position.
Pros: Rated ‘E’ for everyone. This tutorial is one I have used myself! It includes code snippets to learn from.
Cons: It is a tutorial, not a cheat sheet to print.
Cheat Sheet 10: FullStack Python
This is also a tutorial for you to learn from. This particular cheat sheet discusses Deployment of web applications in Python!! It has explanations that go into depth with tools, resources and learning checklist which is started off with an introductory on deployment what it is and why it is necessary.
Pros: Rated ‘E’ for everyone. This is important to know if you are a Pythoner in Web development.
Cons: Needs to be bookmarked on your browser.
These are the cheat sheets and tutorials I think you will find helpful as a Pythonista developing in your particular field. As you can see this time, I wanted to really give you a wide berth of cheat sheets that intermediate Pythonista use with their career choices. I hope at least one of these cheat sheets or tutorials is useful to you on your journey! Thank you once again for joining me and I can’t wait to see you again! 😉😉
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The SQL cheat sheet provides you with the most commonly used SQL statements for your reference. You can download the SQL cheat sheet as follows:
Querying data from a table
Query data in columns c1, c2 from a table
Query all rows and columns from a table
Query data and filter rows with a condition
Query distinct rows from a table
Sort the result set in ascending or descending order
Skip offset of rows and return the next n rows
Group rows using an aggregate function
Filter groups using HAVING clause
Querying from multiple tables
Inner join t1 and t2
Left join t1 and t1
Right join t1 and t2
Perform full outer join
Produce a Cartesian product of rows in tables
Another way to perform cross join
Join t1 to itself using INNER JOIN clause
Pandas Python Dataframe Cheat Sheet
Using SQL Operators
Cities: skylines download free. Combine rows from two queries
Return the intersection of two queries
Subtract a result set from another result set
Query rows using pattern matching %, _
Query rows in a list
Query rows between two values
Check if values in a table is NULL or not
Managing tables
Create a new table with three columns
Delete the table from the database
Add a new column to the table
Drop column c from the table
Add a constraint
Drop a constraint
Rename a table from t1 to t2
Rename column c1 to c2
Remove all data in a table
Using SQL constraints
Set c1 and c2 as a primary key
Set c2 column as a foreign key
Make the values in c1 and c2 unique
Ensure c1 > 0 and values in c1 >= c2
Set values in c2 column not NULL
Modifying Data
Insert one row into a table
Insert multiple rows into a table
Insert rows from t2 into t1
Update new value in the column c1 for all rows
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Update values in the column c1, c2 that match the condition
Delete all data in a table
Delete subset of rows in a table
Managing Views
Create a new view that consists of c1 and c2
Create a new view with check option
Create a recursive view
Create a temporary view
Delete a view
Managing indexes
Create an index on c1 and c2 of the t table
Create a unique index on c3, c4 of the t table
Drop an index
Datacamp Sql Cheat Sheet Free
Managing triggers
Create or modify a trigger
WHEN
- BEFORE – invoke before the event occurs
- AFTER – invoke after the event occurs
EVENT
- INSERT – invoke for INSERT
- UPDATE – invoke for UPDATE
- DELETE – invoke for DELETE
TRIGGER_TYPE
- FOR EACH ROW
- FOR EACH STATEMENT
Delete a specific trigger