Catalog

• One 、pandas brief introduction
• Two 、Series
• • 1 - Series brief introduction
  • 2 - Series establish
  • 3 - Series Index and slice of
  • 4 - Series Common properties
  • 5 - Series Common methods
• 3、 ... and 、DataFrame
• • 1 - Dataframe brief introduction
  • 2 - DataFrame establish
  • 3 - DataFrame Properties of
  • 4 - DataFrame Indexes
  • 5 - DataFrame section
  • 6 - Time data type conversion
  • 7 - Set a column as a row index
• Four 、jupyter note

One 、pandas brief introduction

• Why study pandas：numpy It can already help us with data processing , So learning pandas What is the purpose of ？
  • numpy What can help us deal with is numerical data , Of course, there are many other types of data besides numerical data in data analysis （ character string , The time series ）, that pandas It can help us deal with other data except numerical data
• pandas Two classes commonly used in
  • Series
  • DataFrame

Two 、Series

1 - Series brief introduction

• What is? Series：Series Is an object similar to a one-dimensional array , It's made up of two parts
  • values： A set of data （ndarray type ）
  • index： Related data index labels

2 - Series establish

• Series Two ways to create
  • From list or numpy Array creation
  • Created by dictionary

3 - Series Index and slice of

4 - Series Common properties

• Series Common properties
  • shape： shape
  • size： Element number
  • index： Returns the index
  • values： Return value
  • dtype： Type of element
    

5 - Series Common methods

• Common methods
  • head(),tail()
  • unique()
  • isnull(),notnull()
  • add() sub() mul() div()

3、 ... and 、DataFrame

1 - Dataframe brief introduction

• What is? DataFrame：DataFrame It's a 【 Tabular form 】 Data structure of .DataFrame It consists of multiple columns of data arranged in a certain order . The original intention of the design is to Series From one dimension to multi dimension .DataFrame Existing row index , There are also column indexes
• DataFrame structure ： It can be understood as a table in the database
  • Row index ：index
  • Column index ：columns
  • value ：values

2 - DataFrame establish

• DataFrame Two ways to create
  • ndarray establish
  • Dictionary creation

3 - DataFrame Properties of

• DataFrame Common properties ：values、columns、index、shape

• practice ： According to the following test scores , Create a DataFrame, Name it df

 Zhang San Li Si
Chinese language and literature 150 0
mathematics 150 0
English 150 0
Synthesis 300 0

4 - DataFrame Indexes

• Single column 、 Take multiple columns

• Take single line 、 Take multiple lines
  
• loc and iloc The difference between ： Reference material
  • iloc： Fetching rows by implicit index
  • loc： Fetching rows by explicit index
• Take a single element 、 Take multiple elements
  

5 - DataFrame section

• Yes 、 Slice columns
  

• practice ： Index slice ：

  • ①. hypothesis ddd It's the midterm exam result ,ddd2 It's the final exam result , Please create freely ddd2, And with ddd Add up , Find the average value at the end of the interim period
  • ②. Suppose that Zhang 3 was found cheating in the mid-term examination of Mathematics , Remember as 0 branch , How to achieve ？
  • ③. Li Si makes contributions for reporting Zhang San's cheating , Midterm all subjects plus 100 branch , How to achieve ？
  • ④. Later, the teacher found that a problem had gone wrong , In order to appease the students , Add... To every student and subject 10 branch , How to achieve ？

DataFrame The operation rules of are the same as Series

6 - Time data type conversion

• pd.to_datetime(col)

7 - Set a column as a row index

• df.set_index()

Four 、jupyter note

Click to download jupyter note