Layers methods

Get layer information

To get layer’s tag or description:

omi.layers['foo_layer'].tag
omi.layers['foo_layer'].info

When adding new layer, omilayers assigns na as layer’s tag and description. To set this kind of information to a layer:

omi.layers['foo_layer'].set_tag("data") # tag can be an arbritary string.
omi.layers['foo_layer'].set_info("This is the updated description.")

Get layer columns

omi.layers['foo_layer'].columns

Load layer data

To load all columns of layer as pandas.DataFrame

omi.layers['foo_layer'].to_df()

# Add layer column as pandas.DataFrame index
omi.layers['foo_layer'].to_df(index='colA')

To load specific columns of layer as pandas.DataFrame

omi.layers['foo_layer']['colA']
omi.layers['foo_layer'][['colA', 'colB']]
omi.layers['foo_layer'][0] # index of column
omi.layers['foo_layer'][0:10] # slice of columns indices

Conditional layer data load

To load all or certain columns from layer where column colB has value foo it can be done with the following ways:

  1. Using the .loc method:

omi.layers['foo_layer'].loc[["foo"], ['col1', 'col2'], 'colB']

Note

By default, .loc searches for values in the rowid. To specify the column where the values will be searched, pass the name of the column as a third argument.

Parse the first three rows for a set of columns

omi.layers['foo_layer'].loc[[0,1,2], ['col1', 'col2']]

  1. Using the .query method:

# Select all columns where colB has some value
omi.layers['foo_layer'].query("colB == 0")
omi.layers['foo_layer'].query("colB == 'someString'")

# Select columns colA and colC where colB has some value
omi.layers['foo_layer'].query("colB == 'someString'", cols=['colA', 'colC'])

  1. For more complex queries use the “.select” method:

# cols="*" selects all columns
omi.layers['foo_layer'].select(cols="*", where="colB", values=0)
omi.layers['foo_layer'].select(cols="*", where="colB", values="string")
omi.layers['foo_layer'].select(cols="*", where="colB", values=[1,2,3,4])
omi.layers['foo_layer'].select(cols="*", where="colB", values=np.arange(1,10))

# To exclude a column from selection
omi.layers['foo_layer'].select(cols="*", exclude="colC", where="colB", values=np.arange(1,10))
omi.layers['foo_layer'].select(cols="*", exclude=["colC", "colD"], where="colB", values=np.arange(1,10))

# To select specific columns
omi.layers['foo_layer'].select(cols="colC", where="colB", values=np.arange(1,10))
omi.layers['foo_layer'].select(cols=["colC", "colD"], where="colB", values=np.arange(1,10))

Add or update layer column data

The code below:

data = np.arange(1,10)
data = pd.Series(np.arange(1,10))
data = [1,2,3,4,5,6,7,8,10]
omi.layers['foo_layer']['colA'] = data

will add colA to layer foo_layer if colA does not exist. Otherwise, it will replace the data colA holds.

Rename layer column

To rename layer’s column name from colA to colB:

omi.layers['foo_layer'].rename(col="colA", new_name="colB")

Delete layer column or rows

To delete the entire column colA from layer:

omi.layers['foo_layer'].drop("colA")

To delete rows where colA has certain value(s):

omi.layers['foo_layer'].drop("colA", values=0)
omi.layers['foo_layer'].drop("colA", values="string")
omi.layers['foo_layer'].drop("colA", values=[1,2,3,4])

To delete rows based on their rowids:

omi.layers['foo_layer'].drop(values=0)
omi.layers['foo_layer'].drop(values=[0,1,2,3])

Note

When deleting rowids, the values should be integers.

Replace all layer data

To replace the data of a layer:

new_data = pd.DataFrame({"col1":[1,2,3,4], "col2":[10,20,30.40]})
omi.layers['foo_layer'].set_data(new_data)

Insert rows to layer

To insert new rows to an existing layer it can be done with two ways:

  1. using a dictionary

data = {"col1":[1,2,3,4], "col2":[10,20,30,40]}
omi.layers['foo_layer'].insert(data)

Note

The names of the dictionary’s keys should match column names in the layer.

  1. using a pandas.DataFrame

data = pd.DataFrame({"col1":[1,2,3,4], "col2":[10,20,30.40]})

# Column order in data does not match order in layer.
omi.layers['foo_layer'].insert(data)

# Column order in data matches order in layer.
omi.layers['foo_layer'].insert(data, ordered=True)

Create json with layer columns

To create a python dictionary with keys the values of column colA and values the values of column colB of a layer:

omi.layers['foo_layer'].to_json(key_col="colA", value_col="colB")

Join layers

omilayers loads data as pandas.DataFrame objects. Thus, to join two layers that have the column id in common the pandas.concat method can be used.

dfJoined = pd.concat([
                     omi.layers['layer1'].to_df(index='id'),
                     omi.layers['layer2'].to_df(index='id')
                    ], axis='columns')

or to filter layers before joining

dfJoined = pd.concat([
                     omi.layers['layer1'].query(f"id BETWEEN 10 AND 100").set_index("id"),
                     omi.layers['layer2'].query(f"id BETWEEN 10 AND 100").set_index("id")
                    ], axis='columns')