Pandas数据过滤的多种方式

DataFrame方式 import pandas as pd df = pd.read_csv("data.csv", header=1, names=["index","id","url"]) df.dropna(how="any", inplace=True) # DataFrame方式 newdf1 = df[(df.id == 4099963) | (df.id == 5181745)] print("newdf1:", newdf1) 查询函数 # 查询函数 newdf2 = df.query("id == 4099963 | id == 5181745") print("newdf2:", newdf2) loc函数 # loc函数 newdf3 = df.loc[(df.id == 4099963) | (df.id == 5181745)] print("newdf3:", newdf3) iloc函数 # 行列筛选 newdf4 = df.iloc[1:5, :4] print("newdf4:", newdf4) 非空 # 非空 newdf5 = df[df.url.notnull()] 字符串 # str newdf6 = df[df.url.str.contains("https")] print(newdf6) apply # apply newdf7 = df[df.apply(lambda x: len(x["url"]) > 10, axis=1)] print(newdf7) 参考

https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html
http://www.360doc.com/document/23/0624/20/82716111_1086091874.shtml