Python项目–使用Python进行数据分析

学习数据分析，走向学习数据科学，在本课程中，我们上传了8个数据分析项目，都是用Python解决的。如果你想找一份数据分析师的初级工作，可以使用这些项目。如果你是学生，你可以使用这些项目在学院/研究所提交。源代码和数据集文件可以下载。所有的项目都有一个非常简单的解释。我们主要使用流行的Python Pandas库和Matplotlib来解决这些项目。Python Projects – Data Analytics With Python

这些项目是:项目1 -天气数据分析项目2 -汽车数据分析项目3 -警方数据分析项目4 – Covid数据分析项目5 -伦敦住房数据分析项目6 -人口普查数据分析项目7 – Udemy数据分析项目8 -网飞数据分析这些项目中使用的一些基本命令示例有:* head() -它显示数据中的前N行(默认情况下，N=5)。* shape -它显示数据帧的总行数和列数* index -此属性提供数据帧*列的索引-它显示每列的名称* dtypes -它显示每列的数据类型* unique() -在一列中，它显示所有唯一值。它只能应用于单个列，而不能应用于整个数据帧。* nunique() -显示每列中唯一值的总数。它可以应用于单个列，也可以应用于整个数据帧。* count -显示每列中非空值的总数。它可以应用于单个列，也可以应用于整个数据帧。* value_counts -在一列中，显示所有唯一值及其计数。它只能应用于单个列。* info() -提供关于数据帧的基本信息。* size -显示数据集中总值(元素)的数量。* duplicated( ) -逐行检查并检测重复的行。* isnull( ) -显示空值出现的位置。* dropna( ) -删除包含所有缺失值的行。* isin( ) -显示包括特定元素的所有记录。* str.contains( ) -获取包含给定字符串的所有记录。* str.split( ) -它将一列的字符串拆分成不同的列。* to_datetime( ) -将日期时间列的数据类型转换为datetime[ns]数据类型。* dt.year.value_counts( ) -计算时间列中所有年份的出现次数。* groupby( ) – Groupby用于根据某些标准将数据分成不同的组。* SNS . count plot(df[‘ Col _ name ‘])-以条形图的形式显示任何列的所有唯一值的计数。* max()，min( ) -显示系列的最大/最小值。* mean( ) -显示系列的平均值。

MP4 |视频:h264，1280×720 |音频:AAC，44.1 KHz
语言:英语|大小:1.98 GB 含课程文件 |时长:4小时 16分钟

你会学到什么
Python库——Pandas、Matplotlib、Numpy
Python编程语言
基础数据科学
用Python解决数据分析项目
所有项目都已解决，并且可以使用Python源代码文件和数据集文件
这些项目可以用于简历/CV，大学提交

要求
初学者友好的项目-只需要基本的Python语言知识
你可以使用Jupyter notebook，Google Colab等来运行python代码
本课程提供所有数据集和源代码下载
这门课程既适合初学者，也适合中级水平…你会喜欢的。

目录：
第1部分:Python数据分析项目

第1讲项目1 -天气数据分析

第2讲项目2 -汽车数据分析

第3讲项目3 -警察数据分析

第4讲项目4 -新冠肺炎数据分析

第5讲项目5 -伦敦住房数据分析

第6讲项目6 -普查数据分析

第7讲项目7 – Udemy数据分析

第8讲项目8 -网飞数据分析

寻找数据分析师工作的初学者，在学院/研究所搜索项目的学生，任何对数据科学和数据分析感兴趣的人

Learn Data Analysis and move towards learning Data Science

What you’ll learn
Python Libraries – Pandas, Matplotlib, Numpy
Python Programming Language
Basic Data Science
Data Analytics Projects solved with Python
All projects are Solved, and available with Python Source Codes files & dataset files
These projects can be used in Resume/CV, college submission

Requirements
Beginners Friendly Projects – Required only basic Python language knowledge
You can use Jupyter notebook, Google Colab etc to run the python code
All datasets & source codes are available to download with this course
This course is for beginners as well as intermediate level … You will enjoy it.

Description
In this course, we have uploaded 8 Data Analytics Projects, solved with Python.These projects can used if you are looking for a starting level job as a Data Analyst.If you are a student, you can use these projects to submit in college/institute.The source codes and datasets files are available to download.All the projects are created with a very easy explanation.We have mainly used the popular Python Pandas Library, along with Matplotlib to solve these projects.To buy our Data Analyst Study Material , you can mail us at datasciencelovers@gmail.comThe projects are :Project 1 – Weather Data AnalysisProject 2 – Cars Data AnalysisProject 3 – Police Data AnalysisProject 4 – Covid Data AnalysisProject 5 – London Housing Data AnalysisProject 6 – Census Data AnalysisProject 7 – Udemy Data AnalysisProject 8 – Netflix Data AnalysisSome basic examples of commands used in these projects are :* head() – It shows the first N rows in the data (by default, N=5).* shape – It shows the total no. of rows and no. of columns of the dataframe* index – This attribute provides the index of the dataframe* columns – It shows the name of each column* dtypes – It shows the data-type of each column* unique() – In a column, it shows all the unique values. It can be applied on a single column only, not on the whole dataframe.* nunique() – It shows the total no. of unique values in each column. It can be applied on a single column as well as on the whole dataframe.* count – It shows the total no. of non-null values in each column. It can be applied on a single column as well as on the whole dataframe.* value_counts – In a column, it shows all the unique values with their count. It can be applied on a single column only.* info() – Provides basic information about the dataframe.* size – To show No. of total values(elements) in the dataset.* duplicated( ) – To check row wise and detect the Duplicate rows.* isnull( ) – To show where Null value is present.* dropna( ) – It drops the rows that contains all missing values.* isin( ) – To show all records including particular elements.* str.contains( ) – To get all records that contains a given string.* str.split( ) – It splits a column’s string into different columns.* to_datetime( ) – Converts the data-type of Date-Time Column into datetime[ns] datatype.* dt.year.value_counts( ) – It counts the occurrence of all individual years in Time column.* groupby( ) – Groupby is used to split the data into groups based on some criteria.* sns.countplot(df[‘Col_name’]) – To show the count of all unique values of any column in the form of bar graph.* max( ), min( ) – It shows the maximum/minimum value of the series.* mean( ) – It shows the mean value of the series.

Overview
Section 1: Python Data Analytics Projects

Lecture 1 Project 1 – Weather Data Analysis

Lecture 2 Project 2 – Cars Data Analysis

Lecture 3 Project 3 – Police Data Analysis

Lecture 4 Project 4 – Covid-19 Data Analysis

Lecture 5 Project 5 – London Housing Data Analysis

Lecture 6 Project 6 – Census Data Analysis

Lecture 7 Project 7 – Udemy Data Analysis

Lecture 8 Project 8 – Netflix Data Analysis

Beginners looking for job as a Data Analyst,Students searching for projects to submit in college/institute,Anyone interested in Data Science and Data Analytics