小弟新手，现在在处理一个二百多万的dataset，把他读取成pandas的dataframe后想根据每列特征值的不同做一个分类赋值。可是直接用datafrane做起来很慢，一个数据点都需要两三秒左右。求问有没有什么快捷的办法处理？谢谢！
比如：
price post_code year month property_type whether_new \ 0 0 155000 N20 9AQ 1995 1 F Y 1 1 67500 SE1 4HG 1995 1 F Y 2 2 99950 SE1 0RD 1995 1 S Y 3 3 102000 N3 1AE 1995 1 F N 4 4 100000 W11 1PN 1995 1 S N 5 5 57500 SW4 0NU 1995 1 F N我想把property type里的F全换成'000',s全换成'001'.
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I saw your data, my place is very fast, it takes less than 1 second to replace all the data:
data.csv contains two million records, which I randomly generated