We will use the data from the world bank. It contains data on world economies for over half a century. The indicators are : Population Electricity consumption CO2 emissions Literacy rates Unemployment Mortality rates Dictionaries for data science+ Writing a function to help you Using a list comprehension Turning this Read more…
Populate a list with a for loop : We can do that in only one line with a list comprehension ! Now a list comprehension with range() : List comprehensions : Collapse for loops for building lists into a single line Components : iterable iterator variable (represent members of iterable) Read more…
There is a ton of built in functions such as str(), type() and so one and so forth. But you can as well define your own functions You can also define parameters for your functions. In the example below value is the parameter and can be passed when we call Read more…
In this section we will implement an algorithm that will emulate the following game : You do a bet with your friend that if you start at the first step of the empire state building and that on each step you roll a dice If you roll 1 or 2 Read more…
Now if we want to repeat things we can use a wide variety of tools. Like : While loops Repeating action until condition is met Do not forget to increment the condition to avoid being stuck in an infinite loop. If your are just ctrl+c to stop the calculation For Read more…
Numpy Recap : Numeric comparison : Other comparisons Boolean Operators and or not With Numpy arrays you can simply use the boolean operators as is you have to use logical methods which are : logical_and() logical_or() logical_not() Conditional Statements if else elif Filtering Pandas DataFrame We take again our brics Read more…
Dictionaries When you have data scattered in multiple list it is not very intuitive to query it. You have to write plenty of useless lines of code, which makes the code unclear and hard to read. Example : We can use a dictionary which agregates stuff into one object : Read more…