From: DBWangGroup 基于该系列代码的实践与补充思考. 补充:特征工程 结合:[Scikit-learn] 4.3. Preprocessing data /* implement */…

From: DBWangGroup 基于该系列代码的实践与补充思考. 补充:特征工程 http://www.cnblogs.com/jasonfreak/category/823064.html  <-- 相当不错 结合:[Scikit-learn] 4.3. Preprocessing data 随机数 产生N个随机数 import random n = 10 data = [random.randint(1, 10) for _ in range(n)] data # this print…

The Dataset was acquired from https://www.kaggle.com/c/titanic For data preprocessing, I firstly defined three transformers: DataFrameSelector: Select features to handle. CombinedAttributesAdder: Add a categorical feature Age_cat which divided all pa…

这段时间用pandas做数据分析, import pandas.io.data as web 然后得到下面的错误提示 "The pandas.io.data module is moved to a separate package " ImportError: The pandas.io.data module is moved to a separate package (pandas-datareader). After installing the pandas-datarea…

0.Principal component analysis (PCA) Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated …

通过MLP多层感知机神经网络训练模型,使之能够根据sonar的六十个特征成功预测物体是金属还是石头.由于是简单的linearr线性仿射层,所以网络模型的匹配度并不高. 这是我的第一篇随笔,就拿这个来练练手吧(O(∩_∩)O). 相关文件可到github下载.本案例采用python编写.(Juypter notebook) 首先导入所需的工具包 1 import numpy as np 2 import pandas as pd 3 import matplotlib.pyplot as plt…

10 Minutes to pandas import pandas as pd import numpy as np import matplotlib.pyplot as plt dates = pd.date_range(', periods=3) # 创建 16 17 18 等六个日期 df = pd.DataFrame(np.random.randn(3,4), index=dates, columns=list('ABCD')) # 这是二维的,类似于一个 df1 = df.rein…

感觉很详细:数据分析:pandas 基础 import pandas as pd import numpy as np import matplotlib.pyplot as plt dates = pd.date_range(', periods=3) # 创建 16 17 18 等六个日期 df = pd.DataFrame(np.random.randn(3,4), index=dates, columns=list('ABCD')) # 这是二维的,类似于一个表! # 通过 numpy…

有很多方法用来集体计算DataFrame的描述性统计信息和其他相关操作. 其中大多数是sum(),mean()等聚合函数. 一般来说,这些方法采用轴参数,就像ndarray.{sum,std,...},但轴可以通过名称或整数来指定: 数据帧(DataFrame) - “index”(axis=0,默认),columns(axis=1) 下面创建一个数据帧(DataFrame),并使用此对象进行演示本章中所有操作. import pandas as pd d = {'Name':pd.Series…

Data Engineering Data  Pipeline Outline [DE] How to learn Big Data[了解大数据] [DE] Pipeline for Data Engineering[工作流案例示范] [DE] ML on Big data: MLlib[大数据的机器学习方案] DE基础(厦大) [Spark] 00 - Install Hadoop & Spark[ing] [Spark] 01 - What is Spark[大数据生态库] [Spark]…