截取某段时间内的数据,如果以date为index,则:
data.index = pd.to_datetime(data.index) data = data[(data.index >=pd.to_datetime('20150511')) & (data.index <= pd.to_datetime('20150611'))]
如果Date为column,则:
data['Date'] = pd.to_datetime(data['Date']) data = data[(data['Date'] >=pd.to_datetime('20120701')) & (data['Date'] <= pd.to_datetime('20120831'))]
对DataFrame中单个cell进行值的更改,需要遵循先column名,后index的原则,否则无法更改其value
data['crest_price']['2015-04-08']=10 # 要把index写在后面就好
选取某一列的字段以“XXX”开头,产生新的字段
MutualFund.loc[[i.startswith('20010101') for i in MutualFund['s_info_sector']],'level1_type'] = '股票型' MutualFund.loc[[i.startswith('20010102') for i in MutualFund['s_info_sector']],'level1_type'] = '混合型'
选择数据中,某一columns的值以某一形式开头的数据有两种方法,1、直接选;2、做一个标记选
1、dt = MutualFund.loc[[i.startswith('20010108') for i in MutualFund['s_info_sector']]]
2、MutualFund['wind_investsect'] = [i.startswith('200101') for i in MutualFund['s_info_sector']]
MutualFund = MutualFund[MutualFund['wind_investsect']==True] # 选择投资风格