Data Science & Python
Python

Python is a programming language widely used by Data Scientists.
It has in-built mathematical libraries and functions,
these made it easier to calculate mathematical problems
and to perform data analysis.

Python Libraries

Python has libraries with huge collections of mathematical
functions and analytical tools.
In this course, we will use the following libraries:

Pandas- This library is used for structured data operations,
like import CSV files, create dataframes, and data preparation

Numpy - This is a mathematical library.
It has a powerful N-dimensional array object,
linear algebra, Fourier transform, etc.

Matplotlib - This library is used for visualization of data.

SciPy - This library has linear algebra modules

Data Science - Python DataFrame

A data frame is a structured representation of data.
We define a data frame with
3 columns and 5 rows
with fictional numbers:


Example
import pandas as pd
d = {'col1': [1, 2, 3, 4, 7],'col2': [4, 5, 6, 9, 5], 'col3': [7, 8, 12, 1, 11]}
df = pd.DataFrame(data=d)
print(df)


Output:


Explaing the Example:

-Import the Pandas library as pd
-Define data with column and rows in a variable named d
-Create a data frame using the function pd.DataFrame()
-The data frame contains 3 columns and 5 rows
-Print the data frame output with the print() function

to activate the DataFrame() function from the Pandas library,
we write pd. in front of DataFrame()


To Interpret the Output:


"col1", "col2" and "col3" are the names of the columns.

the vertical numbers from 0-4, tell us the information about
the position of the rows.

Note that in Python, the numbering of rows starts with zero.

you can use Python to count the columns and rows.

Example

To Count the number of columns:
count_column = df.shape[1]
print(count_column)

import pandas as pd
d = {'col1': [1, 2, 3, 4, 7], 'col2': [4, 5, 6, 9, 5], 'col3': [7, 8, 12, 1, 11]}

We use df.shape[1] to find the number of columns:

df = pd.DataFrame(data=d)
count_column = df.shape[1]
print("Number of columns:")
print(count_column)


Output:
Number of columns:
3

We use df.shape[0] to find the number of rows:

Example

Count the number of rows:
count_row = df.shape[0]
print(count_row)


import pandas as pd
d = {'col1': [1, 2, 3, 4, 7], 'col2': [4, 5, 6, 9, 5], 'col3': [7, 8, 12, 1, 11]}

df = pd.DataFrame(data=d)
count_row = df.shape[0]
print("Number of rows:")
print(count_row)

Output: Number of rows: 5

We can use df.shape[1] to find the number of columms:
We can use df.shape[0] to find the number of rows:



<<< previous .      Next >>>.

Professional courses:

participant -Kids, Youths and Adults alike
learn and aquire these professional Courses

Professional Courses:

Informatiker

Website programming

IT Consultant

IT Security

Java Programming

Software Developer

IT Admin.

IT FORENSIC

Python Programming

programming with C++

Data Science

---

Are you parents, teachers or affiliate schools, pls. click here.

click here to view 'KITAS' arround you

---