Learn the basics of Pandas DataFrames and the most common operations you need to do effective data analysis.
⭐️ Tutorial Contents ⭐️
(01:40) Installing Pandas
(07:00) Check for missing values
(07:38) Remove rows with missing values
(08:43) Check column data types
(08:51) Convert column to datetime
(10:22) List the name of the columns
(10:55) Deleting columns
(12:15) Select a subset of the columns
(13:16) Get all possible values in a column
(13:42) Renaming columns
(14:50) Reordering columns
(15:55) Add new column
(17:02) Select rows based on column value
(18:00) Iterating over rows
Notebook (Google Colab): https://colab.research.google.com/dri…
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Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.
When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,
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This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you’ll be a python programmer in no time!
⭐️ Contents ⭐
⌨️ (0:00) Introduction
⌨️ (1:45) Installing Python & PyCharm
⌨️ (6:40) Setup & Hello World
⌨️ (10:23) Drawing a Shape
⌨️ (15:06) Variables & Data Types
⌨️ (27:03) Working With Strings
⌨️ (38:18) Working With Numbers
⌨️ (48:26) Getting Input From Users
⌨️ (52:37) Building a Basic Calculator
⌨️ (58:27) Mad Libs Game
⌨️ (1:03:10) Lists
⌨️ (1:10:44) List Functions
⌨️ (1:18:57) Tuples
⌨️ (1:24:15) Functions
⌨️ (1:34:11) Return Statement
⌨️ (1:40:06) If Statements
⌨️ (1:54:07) If Statements & Comparisons
⌨️ (2:00:37) Building a better Calculator
⌨️ (2:07:17) Dictionaries
⌨️ (2:14:13) While Loop
⌨️ (2:20:21) Building a Guessing Game
⌨️ (2:32:44) For Loops
⌨️ (2:41:20) Exponent Function
⌨️ (2:47:13) 2D Lists & Nested Loops
⌨️ (2:52:41) Building a Translator
⌨️ (3:00:18) Comments
⌨️ (3:04:17) Try / Except
⌨️ (3:12:41) Reading Files
⌨️ (3:21:26) Writing to Files
⌨️ (3:28:13) Modules & Pip
⌨️ (3:43:56) Classes & Objects
⌨️ (3:57:37) Building a Multiple Choice Quiz
⌨️ (4:08:28) Object Functions
⌨️ (4:12:37) Inheritance
⌨️ (4:20:43) Python Interpreter
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=rfscVS0vtbw&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=3
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Pandas is one of the predominant data analysis tools which is highly appreciated among data scientists. It provides numerous flexible and versatile functions to perform efficient data analysis.
In this article, we will go over 3 pandas tricks that I think will make you a more happy pandas user. It is better to explain these tricks with some examples. Thus, we start by creating a data frame to wok on.
The data frame contains daily sales quantities of 3 different stores. We first create a period of 10 days using the
date_range function of pandas.
import numpy as np import pandas as pd days = pd.date_range("2020-01-01", periods=10, freq="D")
The days variable will be used as a column. We also need a sales quantity column which can be generated by the
randint function of numpy. Then, we create a data frame with 3 columns for each store.
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If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.
However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:
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