Cannot understand ValueError for pandas.HDFStore.select(), HDF5 from Pytables
This is a standard Python error, but I don't understand it in this context:

I have an HDF5 object I create with Pytables. Printing out the information in Python with `>>> store`, I see the following information

    import pandas as pd
    store = pd.HDFStore("file.h5")
    >>> store 
    
    <class 'pandas.io.pytables.HDFStore'>
    File path: /path/pathname/file.h5
    given_key           frame_table [0.0.0] (typ->generic,nrows->877129127,ncols->6,indexers->[index],dc->[COL1, COL2, COL3, COL4, COL5, COL6])
    
    So, there are 6 columns and 877 million rows. I indexed on COL1 and COl6. 

Now, I'm getting errors when I try to select values. 

    df = store.select(key ="given_key", columns = "COL1", start=0, stop=1)  

This outputs the error: 

    ValueError: Shape of passed values is (1, 1), indices imply (1, 877129127)

So I try this:

    df = store.select(key ="given_key", start=0, stop=1)  

I get the same ValueError

    ValueError: Shape of passed values is (1, 1), indices imply (1, 877129127)

What does this mean? Is there an error in terms of how I created this HDF5 object? 


Let's say I want a value which I know exists in `COL1`

    df = store.select("given_key", where = "COL1 == 'abc'")

Here's the error I get: 

    ValueError: Shape of passed values is (1, 1231), indices imply (1, 877129127)

It looks like it has accessed 1231 rows with this query value (which makes sense) but I cannot....get it. 

How can I fix this? 
