CSV#
Overview#
Data structure support |
-- |
CSV is used to store tabular data, but unlike other serialisation formats reviewed here, it’s not suitable for (nested) objects. |
Standardisation |
-- |
CSV is not well standardised: neither the encoding is defined nor the separation of the cell contents (comma, semicolon etc.). |
Schema IDL |
-- |
No |
Language support |
++ |
The CSV format is well supported by almost every
programming language. A csv module is included in
the Python standard library and pandas can read a
CSV file straight into a Even if CSV is the only format described here that is well supported by spreadsheet programs like Excel, you should see if you can import more structured Excel files directly, e.g. with pandas read_excel. |
Human readability |
+- |
CSV is readable especially for integer or decimal numbers with the same character length. In all other cases it will be difficult to identify the corresponding columns. |
Speed |
+ |
CSV is very fast to serialise and deserialise. |
File size |
++ |
Only Protocol Buffers (Protobuf) should be more compact. |
Example#
5.1,0.222222222,3.5,0.625,1.4,0.06779661,0.2,0.041666667,setosa
4.9,0.166666667,3,0.416666667,1.4,0.06779661,0.2,0.041666667,setosa
4.7,0.111111111,3.2,0.5,1.3,0.050847458,0.2,0.041666667,setosa
4.6,0.083333333,3.1,0.458333333,1.5,0.084745763,0.2,0.041666667,setosa
5,0.194444444,3.6,0.666666667,1.4,0.06779661,0.2,0.041666667,setosa
...