python - How to look up values from another dataset with Tensorflow? -


i got 2 csv datasources. need doing data formatting before building model.

===============================================

datasource 1: plant.csv

the features of different plants.

plantid, int / plantname, str / color, str /  size, float / cost, float / category, int / weight, float / expire, int / status, int  

datasource 2: [201601.csv, 201602.csv, 201603.csv....]

monthly order sales of plants

plantid, int / salesperson, str / date, datetime / qty, int / price, float / gardener, str / package1, bool / package2, bool / package3, bool 

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now going join files single file this:

plantid, int / plantname, str / color, str /  size, float / cost, float / category, int / weight, float / expire, int / status, int / salesperson, str / date, datetime / qty, int / price, float / gardener, str / package1, bool / package2, bool / package3, bool 

which plantid key.

there millions of sales records each month.

could advise how make tensorflow?

tensorflow not joining databases. if want in python can use pandas.

import pandas pd   df1 = pd.read_csv('plant.csv') df1.set_index(['plantid']) df2 = pd.read_csv('201601.csv') df2.set_index(['plantid'])  df3 = pd.concat([df1, df2], axis=1) 

tensorflow creating computational graphs , running them efficiently. in general assume inputs graph numpy array.

pandas made work relational data inside python in relational database. although if have option of working inside actual relational database query language still more computationally efficient pandas.


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