pandas - 如何仅将 DataFrame 的选定列保存到 HDF5
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pandas - How to save only selected columns of a DataFrame to HDF5
提问by Fabio Lamanna
I'm reading a csv sample file and store it on .h5 database. The .csv is structured as follows:
我正在读取 csv 示例文件并将其存储在 .h5 数据库中。.csv 的结构如下：
User_ID;Longitude;Latitude;Year;Month;String
267261661;-3.86580025;40.32170825;2013;12;hello world
171255468;-3.83879575;40.05035005;2013;12;hello world
343588169;-3.70759531;40.4055946;2014;2;hello world
908779052;-3.8356385;40.1249459;2013;8;hello world
289540518;-3.6723114;40.3801642;2013;11;hello world
635876313;-3.8323166;40.3379393;2012;10;hello world
175160914;-3.53687933;40.35101274;2013;12;hello world
155029860;-3.68555076;40.47688417;2013;11;hello world
I've putting it on a .h5 store with the pandas to_hdf, selecting to pass to the .h5 only a couple of columns:
我已经把它和Pandas to_hdf 放在一个 .h5 存储中，选择只传递给 .h5 几列：
import pandas as pd
df = pd.read_csv(filename + '.csv', sep=';')
df.to_hdf('test.h5','key1',format='table',data_columns=['User_ID','Year'])
I've obtained different results in the columns stored in the .h5 file using HDFStore and read_hdf, in particular:
我使用 HDFStore 和 read_hdf 在 .h5 文件中存储的列中获得了不同的结果，特别是：
store = pd.HDFStore('test.h5')
>>> store
>>> <class 'pandas.io.pytables.HDFStore'>
File path: /test.h5
/key1 frame_table (typ->appendable,nrows->8,ncols->6,indexers->[index],dc->[User_ID,Year])
which is what I expect (only the 'User_ID' and 'Year' columns stored in the database), althought the ncols->6 means that actually all the columns have been stored in the .h5 file.
这是我所期望的（仅存储在数据库中的“User_ID”和“Year”列），尽管 ncols->6 意味着实际上所有列都已存储在 .h5 文件中。
If I try reading the file with pd.read_hdf:
如果我尝试使用 pd.read_hdf 读取文件：
hdf = pd.read_hdf('test.h5','key1')
and asking for the keys:
并要求钥匙：
hdf.keys()
>>> Index([u'User_ID', u'Longitude', u'Latitude', u'Year', u'Month', u'String'], dtype='object')
which is not what I'm expected since all columns of the original .csv file are still in the .h5 database. How can I store only a selection of columns in the .h5 in order to reduce the size of the database?
这不是我所期望的，因为原始 .csv 文件的所有列仍在 .h5 数据库中。如何仅在 .h5 中存储选定的列以减小数据库的大小？
Thanks for your help.
谢谢你的帮助。
回答by Paul H
just select out the columns as you write to the file.
只需在写入文件时选择列。
cols_to_keep = ['User_ID', 'Year']
df[cols_to_keep].to_hdf(...)
