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文章目录1.后裔弃兵2.万恶之源弹幕python3.8jupyter notebook1.后裔弃兵《后翼弃兵》豆瓣短评数据集import pandasimport csvimport jiebaimport numpyfrom PIL import Imagefrom wordcloud import WordClouddef getDataFromCsv(): # 设置星级等级，根据等级来定位提取弹幕 stars = ("1","2","3","4","5")

Market_sales = df.groupby(["Market"]).agg({"Sales":"sum"})Market_Year_Sales = df.groupby(["Market","year"]).agg({"Sales":"sum"}).reset_index().rename(columns={"Sales":"Sales_amounts"})#pandas引入了agg函数，它提供基于列的聚合操作。而groupby可以看做是基于行，或者说index的聚合操作...

1.df表格一列按内容拆分成多列采用onehot拆分df1 = pd.get_dummies(df_test['product_category'])df_test = pd.concat([df_test,df1],axis=1)for cg in range(1,19): df_test[cg] = df_test[cg]*df_test['click_times']df_test=df_test.drop(['product_category','click_times'], 1,

df_log.info(verbose=True,null_counts=True)显示dataframe表格时，可以设置参数，verbose=True：表示设置运行的时候显示详细信息，可选Falsenull_counts=True:缺失值显示，常用

numpy-中文教程https://www.yiibai.com/numpy/