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Data Types in Python
course content

Course Content

Data Types in Python

Data Types in Python

1. Getting Familiar With Numbers in Python
Numerical Data Type in GeneralMutable or Immutable?Integer NumbersCompulsory MathComplicated MathTime CalculationHow to Define a Type
2. True or False?
Introduction to Boolean Data TypeLogical StatementsAnd, Or, Not OperatorsBoost Your Logical SkillsDealing With Not StatementWork With Logical StatementsPriorities
3. Strings
Print Your StringQuotation MarksGet Acquainted With IndexationSlice the WordNegative IndexationSlice the PhraseSlicing TaskHow to Find the String LengthGet the Index of the SymbolFind the Word IndexSlicing with Index FunctionIs String Mutable?Merge Strings
4. Bring All the Topics Together
Convert TypesUseful ConvertingConverting: float()Converting: bool()Converting: str()Math in StringsCompare Strings

Converting: float()

Given that we have already acquired an understanding of the int() operation, it is unnecessary to reiterate the same information. The float() function serves a similar purpose, with the distinction of converting data into the floating-point data type.Look at this simple example:😁


              
1234567

            
variable1 = 56
variable2 = "98.7"
variable3 = "5e4"

print(float(variable1))
print(float(variable2))
print(float(variable3))
copy

It seems to me that one fascinating feature of the float() function should be noted. Not only can we represent regular numbers, but we can also represent concepts like infinity and Not a Number (NaN).

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 4. Chapter 3
toggle bottom row

Converting: float()

Given that we have already acquired an understanding of the int() operation, it is unnecessary to reiterate the same information. The float() function serves a similar purpose, with the distinction of converting data into the floating-point data type.Look at this simple example:😁


              
1234567

            
variable1 = 56
variable2 = "98.7"
variable3 = "5e4"

print(float(variable1))
print(float(variable2))
print(float(variable3))
copy

It seems to me that one fascinating feature of the float() function should be noted. Not only can we represent regular numbers, but we can also represent concepts like infinity and Not a Number (NaN).

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 4. Chapter 3
toggle bottom row

Converting: float()

Given that we have already acquired an understanding of the int() operation, it is unnecessary to reiterate the same information. The float() function serves a similar purpose, with the distinction of converting data into the floating-point data type.Look at this simple example:😁


              
1234567

            
variable1 = 56
variable2 = "98.7"
variable3 = "5e4"

print(float(variable1))
print(float(variable2))
print(float(variable3))
copy

It seems to me that one fascinating feature of the float() function should be noted. Not only can we represent regular numbers, but we can also represent concepts like infinity and Not a Number (NaN).

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Given that we have already acquired an understanding of the int() operation, it is unnecessary to reiterate the same information. The float() function serves a similar purpose, with the distinction of converting data into the floating-point data type.Look at this simple example:😁


              
1234567

            
variable1 = 56
variable2 = "98.7"
variable3 = "5e4"

print(float(variable1))
print(float(variable2))
print(float(variable3))
copy

It seems to me that one fascinating feature of the float() function should be noted. Not only can we represent regular numbers, but we can also represent concepts like infinity and Not a Number (NaN).

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Switch to desktop for real-world practiceContinue from where you are using one of the options below
Section 4. Chapter 3
Switch to desktop for real-world practiceContinue from where you are using one of the options below
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