本文主要是介绍Chapter 2 Data Exploration，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
目录
1. What is Data：
A. Data Types
B. Record Data
C. Types of Attributes
2. Data Exploration：
A. About Data Quality
B. Preprocessing
① Quality
② Sampling
③ Attribute Selection
④ Dimensionality Reduce
⑤ Discretization：Binning
⑥ Statistics
⑦ Visualization
1. What is Data：
A. Data Types： Document Data、Transaction Data、Graph Data、Sequence Data、Spatial-Temporal Data、Record Data、 Data Matrix
Spatial [ˈspeɪʃl] 空间的
Temporal [ˈtempərəl] 时间的B. Record Data：
Collection of data objects and their attributes
An attribute is a property or characteristic of an Object
A collection of attributes describe an Object
property [ˈprɑːpərti] 特性characteristic [ˌkærəktəˈrɪstɪk] 特征C. Types of Attributes：
① Discrete Attribute and Continus Attribute
② Nominal Attribute and Ordinal Attribute
③ Interval Attribute and Ratio Attribute
Nominal [ˈnɒmɪnl] 名义
Ordinal [ˈɔːrdənl] 序数 Interval [ˈɪntəvl] 区间
Ratio [ˈreɪʃioʊ] 比率2. Data Exploration：
A. About Data Quality： Data in the real world is dirty.
① incomplete: lacking attribute values
② noisy：data errors, outliers
③ inconsistent: discrepancy between duplicate records
outlier [ˈaʊtlaɪər] 离群的， 异常的
discrepancy [dɪsˈkrepənsi] 差异，不一致
duplicate [ˈduːplɪkeɪt] 完全一样的，复制的B. Preprocessing：
① Quality：Handle missing values (Ignore or Estimate)、Remove Outliers、Resolve Confilcts （Merge or Identify)
② Sampling：
Key principle：using a sample will work almost as well as using the entire data sets, if the sample is representative;
A sample is representative if it has approximately the same property as the origin set of data
Types of Sampling：Simple Random Sampling、Sampling without replacement、Sampling with repacement、
Stratified Sampling
Sampling Rate：
③ Attribute Selection：Redundant Attributes and Irrelevant Attributes
stratified [ˈstrætɪfaɪd] 分层的
redundant [rɪˈdʌndənt] 冗余的
irrelevant [ɪˈreləvənt] 无关的④ Dimensionality Reduce：
Reduce the number of attributes by creating a new set of attributes.
⑤ Discretization：Binning
Convert numerical data into categorical data
Divides the range into N intervals
⑥ Statistics：
Center Measurement：Mean、Median
Frequency Distribution：Mode
Variability Measurement：Variance，Standard Devitation
⑦ Visualization：
Visualization is the conversion of data into a visual or tabular format
so that characters of the data and the relations among data items or attributes can be analyzed or reported
Visualization of data is one of the most powerful and appealing techniques for Data Exploration
dimensionality [dɪˌmɛnʃəˈnæləti] 维度
discretization 离散化
binning [ˈbɪnɪŋ] 装箱
categorical [ˌkætəˈɡɔːrɪkl] 分类的
mode 众数
devitation 偏差
tabular [ˈtæbjələr] 表格式的
appealing 吸引人的Examples Of Visualization：
Sea Surface Temperature
Histogram：[ˈhɪstəɡræm] 直方图
Box Plots：方块图
Scatter Plot：散点图
Correlation Matrix：关联矩阵
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