TsTables —— Python下基于PyTables將(高頻)時序數據保存為HDF5文件高效訪問的庫。

# Class to use as the table description
class BpiValues(tables.IsDescription):
    timestamp = tables.Int64Col(pos=0)
    bpi = tables.Float64Col(pos=1)

Use pandas to read in the CSV data
bpi = pandas.read_csv('bpi_2014_01.csv',index_col=0,names=['date','bpi'],parse_dates=True)
f = tables.open_file('bpi.h5','a')
Create a new time series
ts = f.create_ts('/','BPI',BpiValues)
Append the BPI data
ts.append(bpi)
Read in some data
read_start_dt = datetime(2014,1,4,12,00)
read_end_dt = datetime(2014,1,4,14,30)
rows = ts.read_range(read_start_dt,read_end_dt)
rows will be a pandas DataFrame with a DatetimeIndex.</pre>

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