Pandas
来自Jack's Lab
Quick Start
test.csv:
name,time,Humi,Temp,dev_id,mac temphumi,1526197529000000000,39.3,27.0,NOD78783243232,AABBCCDDEEFF temphumi,1526202738000000000,39.3,26.9,NOD78783243232,AABBCCDDEEFF temphumi,1526203290000000000,39.4,26.9,NOD78783243232,AABBCCDDEEFF temphumi,1526203298000000000,39.4,26.9,NOD78783243232,AABBCCDDEEFF temphumi,1526203303000000000,39.4,26.9,NOD78783243232,AABBCCDDEEFF
Python 2.7.14 (default, Sep 23 2017, 22:06:14) [GCC 7.2.0] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pandas as pd >>> d=pd.read_csv('test.csv', date_parser=lambda x: pd.to_datetime(float(x)), index_col='time') >>> d=d.drop(columns=['name']) >>> d Humi Temp dev_id mac time 2018-05-13 07:45:29 39.3 27.0 NOD78783243232 AABBCCDDEEFF 2018-05-13 09:12:18 39.3 26.9 NOD78783243232 AABBCCDDEEFF 2018-05-13 09:21:30 39.4 26.9 NOD78783243232 AABBCCDDEEFF 2018-05-13 09:21:38 39.4 26.9 NOD78783243232 AABBCCDDEEFF 2018-05-13 09:21:43 39.4 26.9 NOD78783243232 AABBCCDDEEFF