podpac.data.CSV

class podpac.data.CSV(**kwargs)[source]

Bases: podpac.core.data.datasource.DataSource

Create a DataSource from a .csv file. This class assumes that the data has a storage format such as: header 1, header 2, header 3, … row1_data1, row1_data2, row1_data3, … row2_data1, row2_data2, row2_data3, …

native_coordinates

The coordinates of the data source.

Type

Coordinates

source

Path to the data source

Type

str

alt_col

Column number or column title containing altitude data

Type

str or int

lat_col

Column number or column title containing latitude data

Type

str or int

lon_col

Column number or column title containing longitude data

Type

str or int

time_col

Column number or column title containing time data

Type

str or int

data_col

Column number or column title containing output data

Type

str or int

dims

Default is [‘alt’, ‘lat’, ‘lon’, ‘time’]. List of dimensions tested. This list determined the order of the stacked dimensions.

Type

list[str]

dataset

Raw Pandas DataFrame used to read the data

Type

pd.DataFrame

Methods

__init__(**kwargs)

Do not overwrite me

create_output_array(coords[, data])

Initialize an output data array

eval(coordinates[, output])

Evaluates this node using the supplied coordinates.

eval_group(group)

Evaluate the node for each of the coordinates in the group.

find_coordinates()

Get the available native coordinates for the Node.

get_cache(key[, coordinates])

Get cached data for this node.

get_data(coordinates, coordinates_index)

This method must be defined by the data source implementing the DataSource class.

get_native_coordinates()

Returns a Coordinates object that describes the native coordinates of the data source.

has_cache(key[, coordinates])

Check for cached data for this node.

init()

Overwrite this method if a node needs to do any additional initialization after the standard initialization.

put_cache(data, key[, coordinates, overwrite])

Cache data for this node.

rem_cache(key[, coordinates, mode])

Clear cached data for this node.

Attributes

alt_col

A trait type representing a Union type.

base_definition

Base node defintion for DataSource nodes.

base_ref

Default pipeline node reference/name in pipeline node definitions

cache_ctrl

A trait whose value must be an instance of a specified class.

cache_output

A boolean (True, False) trait.

cache_update

A boolean (True, False) trait.

coordinate_index_type

An enum whose value must be in a given sequence.

data_col

A trait type representing a Union type.

dataset

A trait whose value must be an instance of a specified class.

definition

Full pipeline definition for this node.

dims

An instance of a Python list.

dtype

A trait which allows any value.

hash

interpolation

A trait type representing a Union type.

interpolation_class

Get the interpolation class currently set for this data source.

interpolators

Return the interpolators selected for the previous node evaluation interpolation.

json

definition for this node in json format

json_pretty

lat_col

A trait type representing a Union type.

lon_col

A trait type representing a Union type.

nan_vals

An instance of a Python list.

native_coordinates

A trait whose value must be an instance of a specified class.

pipeline

Create a pipeline node from this node

source

A trait for unicode strings.

style

A trait whose value must be an instance of a specified class.

time_col

A trait type representing a Union type.

units

A trait for unicode strings.

Members

__init__(**kwargs)

Do not overwrite me

alt_col

A trait type representing a Union type.

data_col

A trait type representing a Union type.

dataset

A trait whose value must be an instance of a specified class.

The value can also be an instance of a subclass of the specified class.

Subclasses can declare default classes by overriding the klass attribute

dims

An instance of a Python list.

get_data(coordinates, coordinates_index)[source]

This method must be defined by the data source implementing the DataSource class. When data source nodes are evaluated, this method is called with request coordinates and coordinate indexes. The implementing method can choose which input provides the most efficient method of getting data (i.e via coordinates or via the index of the coordinates).

Coordinates and coordinate indexes may be strided or subsets of the source data, but all coordinates and coordinate indexes will match 1:1 with the subset data.

This method may return a numpy array, an xarray DaraArray, or a podpac UnitsDataArray. If a numpy array or xarray DataArray is returned, podpac.data.DataSource.evaluate() will cast the data into a UnitsDataArray using the requested source coordinates. If a podpac UnitsDataArray is passed back, the podpac.data.DataSource.evaluate() method will not do any further processing. The inherited Node method create_output_array can be used to generate the template UnitsDataArray in your DataSource. See podpac.Node.create_output_array() for more details.

Parameters
  • coordinates (podpac.Coordinates) – The coordinates that need to be retrieved from the data source using the coordinate system of the data source

  • coordinates_index (List) – A list of slices or a boolean array that give the indices of the data that needs to be retrieved from the data source. The values in the coordinate_index will vary depending on the coordinate_index_type defined for the data source.

Returns

A subset of the returned data. If a numpy array or xarray DataArray is returned, the data will be cast into UnitsDataArray using the returned data to fill values at the requested source coordinates.

Return type

np.ndarray, xr.DataArray, podpac.UnitsDataArray

get_native_coordinates()[source]

Returns a Coordinates object that describes the native coordinates of the data source.

In most cases, this method is defined by the data source implementing the DataSource class. If method is not implemented by the data source, it will try to return self.native_coordinates if self.native_coordinates is not None.

Otherwise, this method will raise a NotImplementedError.

Returns

The coordinates describing the data source array.

Return type

podpac.Coordinates

Notes

Need to pay attention to: - the order of the dimensions - the stacking of the dimension - the type of coordinates

Coordinates should be non-nan and non-repeating for best compatibility

The default implementation tries to find the lat/lon coordinates based on dataset.affine or dataset.transform (depending on the version of rasterio). It cannot determine the alt or time dimensions, so child classes may have to overload this method.

lat_col

A trait type representing a Union type.

lon_col

A trait type representing a Union type.

source

A trait for unicode strings.

time_col

A trait type representing a Union type.