How to access a dataframe row?

[Oggy16]

Hi all,

I'm impressed with the performance improvements of the c++ library vs Python pandas, and I'm in looking to migrate over.

One question I've had trouble answering is how to access a single row from a dataframe? In pandas you can do this, but this does not work on this library as the dataframe object is not subscriptable.

I've had a look through the docs and while there seem to be a few ways to access columns, I can't find any to access rows. This makes me think it may be something obvious I am missing.

How do you access an entire row in the dataframe? Best I've found out so far is to access an entire column, and then I can subscript with index.

[aldebaranzbradaradjan]

Hi, I still learn how to use it myself (and don't know anything of panda, anyway it's a good lib and it perform very well, thank hosseinmoein !).
I have had little success with get_row (https://htmlpreview.github.io/?https://github.com/hosseinmoein/DataFrame/blob/master/docs/HTML/get_row.html).
I don't have tested from a while, get_row was ok with the index colum, but i could not get any other column. I don't dig in it. I surely don't use it right at the time.
I just access my data by column instead; If i have a moment i will retry get_row to see how it work now, and open an issue if it look like a bug.

[hosseinmoein]

There are a couple of ways to access data:

1. You can use the get_column method (https://htmlpreview.github.io/?https://github.com/hosseinmoein/DataFrame/blob/master/docs/HTML/get_column.html) which returns a reference to an STL vector. Once you have the reference, you can index through rows or do whatever you could do with an STL vector
2. You can use the get_row method (https://htmlpreview.github.io/?https://github.com/hosseinmoein/DataFrame/blob/master/docs/HTML/get_row.html) which returns a heterogeneous vector. See the doc.

I also recommend going through the hello_world.cc file (https://github.com/hosseinmoein/DataFrame/blob/master/examples/hello_world.cc) in some details

[Oggy16]

Thank you very much. No idea how I missed that in the documentation. It is a bit more convoluted to do than on Python Pandas, but I put that down to my unfamiliarity with C++. Thank you very much for answering my question!

[hosseinmoein]

Yes, unfortunately there is no free lunch. Python is dynamically typed (types are figured out at runtime). That's why Pandas' interface is very elegant and straightforward. C++, on the other hand, is statically typed (all types must be known at compile time). That's why C++ interface is a bit more cluttered.
Also, that is why Python is slow and not as scalable compared with C++.

[Oggy16]

I have to agree, especially on the slowness. When I implemented my simplest data-crunching program for testing, the C++ version with your library used 10x less memory, and was a whopping 168x faster then Python/Pandas for the same task. Considering Pandas is implemented in C I was surprised at how much faster it was.

With improvements like that it is worth for me to learn C++ and deal with the convolutions. I am currently working on re-implementing the rest of the project in C++/DataFrame and I will try to minimise the questions that come up during this period :-)