vaex: shift column by n steps

2
votes

I'm preparing a big multivariate time series data set for a supervised learning task and I would like to create time shifted versions of my input features so my model also infers from past values. In pandas there's the shift(n) command that lets you shift a column by n rows. Is there something similar in vaex?

I could not find anything comparable in the vaex documentation.

2
pythonvaex

2 Answers

5
votes

No, we do not support that yet (https://github.com/vaexio/vaex/issues/660). Because vaex is extensible (see http://docs.vaex.io/en/latest/tutorial.html#Adding-DataFrame-accessors) I thought I would give you the solution in the form of that:

import vaex
import numpy as np

@vaex.register_dataframe_accessor('mytool', override=True)
class mytool:
    def __init__(self, df):
        self.df = df

    def shift(self, column, n, inplace=False):
        # make a copy without column
        df = self.df.copy().drop(column)
        # make a copy with just the colum
        df_column = self.df[[column]]
        # slice off the head and tail
        df_head = df_column[-n:]
        df_tail = df_column[:-n]
        # stitch them together
        df_shifted = df_head.concat(df_tail)
        # and join (based on row number)
        return df.join(df_shifted, inplace=inplace)

x = np.arange(10)
y = x**2
df = vaex.from_arrays(x=x, y=y)
df['shifted_y'] = df.y
df2 = df.mytool.shift('shifted_y', 2)
df2

It generates a single column datagram, slices that up, concatenates and joins it back. All without a single memory copy.

I am assuming here a cyclic shift/rotate.

1
votes

The function needs to be modified slightly in order to work in the latest release (vaex 4.0.0ax), see this thread.

Code by Maarten should be updated as follows:

import vaex
import numpy as np

@vaex.register_dataframe_accessor('mytool', override=True)
class mytool:
    def __init__(self, df):
        self.df = df

    # mytool.shift is the analog of pandas.shift() but add the shifted column with specified name to the end of initial df

    def shift(self, column, new_column, n, cyclic=True):
        df = self.df.copy().drop(column)
        df_column = self.df[[column]]
        if cyclic:
            df_head = df_column[-n:]
        else:
            df_head = vaex.from_dict({column: np.ma.filled(np.ma.masked_all(n, dtype=float), 0)})
        df_tail = df_column[:-n]

        df_shifted = df_head.concat(df_tail)
        df_shifted.rename(column, new_column)

        return df_shifted

x = np.arange(10)
y = x**2
df = vaex.from_arrays(x=x, y=y)
df2 = df.join(df.mytool.shift('y', 'shifted_y', 2))
df2