随笔分类 - 数据分析
摘要：###一. 特征选择 #####1. Permutation Importance # shuffle a single column of the validation data and get the loss(which reflects the importance) import eli5
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摘要：###一. 数据探索分析&数据清洗&缺失值填充 1 Which features are categorical? 什么特征是离散的？ 2 Which features are numerical? 什么特征是连续的？ 3 Which features are mixed data types? 什
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摘要：Pipelines are a simple way to keep your data preprocessing and modeling code organized. Specifically, a pipeline bundles preprocessing and modeling st
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摘要：import matplotlib.pyplot as plt import seaborn as sns ###1. Line Chart plt.figure(figsize=(16,6)) # Set the width and height of the figure plt.title("
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摘要：import numpy as np ###1. Create ndarray #Specify every value x = np.array([1, 2, 3, 4, 5]) y = np.array([[1,2,3],[4,5,6],[7,8,9], [10,11,12]]) # Creat
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摘要：###1. Handling Missing Values #get the missing data ratio missing_values_count = nfl_data.isnull().sum() ## get the number of missing data points per
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摘要：###1. Getting Started import pandas as pd #导入 pd.DataFrame({'Yes': [50, 21], 'No': [131, 2]}) #Create a table #assign the row lables pd.DataFrame({'Bo
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摘要：###1. Function #default values to the functions def greet(who="Colin"): print("Hello,", who) #make choices in the function print("Splitting", total_ca
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摘要：###数据导入 import numpy as np import pandas as pd # 使用pandas读取csv数据，数据类型为dataframe，相当于字典加数组，第一行为索引特征 data = pd.read_csv('data/kaggle_house_price_predicti
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