Loading a csv file

We load a tab separated data file using the load_table() function. The format is inferred from the filename suffix and you will note, in this case, it’s not actually a csv file.

Note

The known filename suffixes for reading are .csv, .tsv and .pkl or .pickle (Python’s pickle format).

Note

If you invoke the static column types argument, i.e.``load_table(…, static_column_types=True)`` and the column data are not static, those columns will be left as a string type.

Loading delimited specifying the format

Although unnecessary in this case, it’s possible to override the suffix by specifying the delimiter using the sep argument.

Loading a set number of lines from a file

If you only want a subset of the contents of a file, use the FilteringParser. This allows skipping certain lines by using a callback function. We illustrate this with stats.tsv, skipping any rows with "Ratio" > 10.

Selectively loading parts of a big file

If you only want a subset of the contents of a file, use the FilteringParser. This allows skipping certain lines by using a callback function. We illustrate this with stats.tsv, skipping any rows with "Ratio" > 10.

Note

You can also negate a condition, which is useful if the condition is complex.

Loading only some columns

Specify the columns by their names.

Or, by their index.

Note

The negate argument does not affect the columns evaluated.

Load raw data as a list of lists of strings

We just use FilteringParser.

Note

The individual elements are still str.

Make a table from header and rows

Make a table from a dict

For a dict with key’s as column headers.

Specify the column order when creating from a dict.

Create the table with an index

A Table can be indexed like a dict if you designate a column as the index (and that column has a unique value for every row).

Note

The index argument also applies when using make_table().

Create a table from a pandas.DataFrame

Create a table from header and rows

Create a table from dict

make_table() is the utility function for creating Table objects from standard python objects.

Create a table from a 2D dict

Create a table that has complex python objects as elements

Create an empty table