latqcdtools.base.cleanData
=============

`clipRange(array, col=None, minVal=-inf, maxVal=inf) -> numpy.ndarray`
 
    Throw out any elements of array that lie outside the interval (minVal,maxVal). Note this
    renders arrays finite. 
    
`deleteCol(array, col) -> numpy.ndarray`

    Remove a column of a 2d np.ndarray.

    Args:
        array (np.ndarray)
        col (int): Remove this column 

    Returns:
        np.ndarray: array with row removed
    
`deleteRow(array, row) -> numpy.ndarray`

    Remove a row of a 2d np.ndarray.

    Args:
        array (np.ndarray)
        row (int): Remove this row 

    Returns:
        np.ndarray: array with row removed
    
`excludeAtCol(table, col=None, atVal=inf) -> numpy.ndarray`
 
    Return everything except those rows of table where col has exactly the value atVal. 
    
`intersectAtCol(table1, table2, col)`
 
    Return only those rows of table1 and table2 that have identical elements in column col. 
    
`restrictAtCol(table, col, atVal, rtol=None, atol=None) -> numpy.ndarray`
 
    Return only those rows of table where col has exactly the value atVal. 
    
`spliceAtCol(table1, table2, col, atVal) -> numpy.ndarray`
 
    Assuming two tables table1 and table2 have common values in column col, create a new
    table, where table1 has corresponding entries less than atVal in col, and table 2
    has corresponding entries greater than atVal.