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I think it would be better to read data from the first row when `colnames` is non-empty. FWIW it is also what [pandas does](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html)…
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Tables.jl interface:
- [x] DTable as a source
- [x] DTable constructors utilizing the interface better if possible - check what is possible and what can be improved
- [x] Schema usage/handling
T…
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I believe that current default is to use most of the available memory on a machine because it gives better performance. However, for various reasons, you might want to use less. E.g. you are sharing t…
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At the moment there's a rather ugly
```julia
X_ = glr.fit_intercept ? hcat(ones(n), X) : X
```
so if `fit_intercept` then potentially the `hcat` creates a new object in memory which is quite i…
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```julia
Table with 8279 rows, 2 columns:
Columns:
[1m# [22m[1mcolname [22mtype
──────────────────
1 1 String
2 2 String
```
This comes up in Juno, for example, where we …
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Sometimes it is useful to read just the first N rows, before reading everything. Is there a recommend way to achieve this?
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Hello, you've done a great job. How does it correspond to Elly?
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I constructed a JuliaDB table and encountered spurious errors. Some times Julia just gets stuck executing code (even calling a `typeof` on the `data` leads the memory to fills up, despite the data set…
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This seems to be more useful generally! I think the cost incurred in the extra allocation is negligible.
We should only keep the table indexed by only those columns for which doing so incurs no fur…
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@nalimilan had a beautiful suggestion here: https://github.com/JuliaData/DataFrames.jl/issues/1514#issuecomment-423222435.
There may actually be very little need to have separate row-wise and colum…