#Load packages

# Read the file & display first 5 rowsimport pandas as pd

import numpy as np

import matplotlib.pyplot as plt6

import seaborn as sns

import warnings

warnings.filterwarnings(“ignore”, category=DeprecationWarning)

warnings.filterwarnings(“ignore”, category=FutureWarning)super_store = pd.read_csv(“D:/ANCHIT/Python/SampleSuperstore.csv”)

super_store.head()

- General Ops — Inverse
- Creation Ops — Complex
- Arithmetic Ops — Transpose
- Mutating Ops — Add
- Reduction Ops — Amax

We will discuss the examples of these 5 Basic functions & observe the errors. Before we begin, let’s install and import PyTorch

# Windows# !pip install numpy torch==1.7.0+cpu torchvision==0.8.1+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html# Import torch and other required modules

import torch

First function we will be using is the ‘Inverse’ function.

`a = torch.randn(2,3,3)`

print(a)

torch.inverse(a)

The above 'randn' function has created 3X3 square matrix with 2 outer most rows. …

**A new and effective way of exploring and analyzing data**

As a Data Scientist, it becomes very important on your part not only to work towards achieving the desired result but also able to understand it. This analyses has to be effectively communicated to your stake holders. Exploratory Data Analyses plays an important role to grab the basic understanding of the data.

In EDA, we perform all the necessary tasks to extract the relevant information out of our data which ranges from performing the tasks related to—

- Finding the Missing/ Null / Nan values
- Performing Statistical Analysis (through describe function)
- …

M.Sc Data Analytics (QUB 2021-22 batch) l Experienced HR Analyst l Travel-freak l French beginner l