pandas.Series.loc¶

Access a group of rows and columns by label(s) or a boolean array.

.loc[] is primarily label based, but may also be used with a boolean array.

Allowed inputs are:

A single label, e.g. 5 or 'a', (note that 5 is
interpreted as a label of the index, and never as an integer position along the index).
A list or array of labels, e.g. ['a', 'b', 'c'].
A slice object with labels, e.g. 'a':'f'.

Warning

Note that contrary to usual python slices, both the start and the stop are included

A boolean array of the same length as the axis being sliced,
e.g. [True, False, True].
A callable function with one argument (the calling Series or
DataFrame) and that returns valid output for indexing (one of the above)

See more at Selection by Label

raises

KeyError:: when any items are not found

Limitations¶

Loc always returns Series.
Loc slice is supported only with numeric values and specified start.
Loc callable is not supported yet.
This function may reveal slower performance than Pandas* on user system. Users should exercise a tradeoff
between staying in JIT-region with that function or going back to interpreter mode.

Examples¶

With a scalar integer. Returns single value.¶

import numpy as np
import pandas as pd
from numba import njit


@njit
def series_loc_value():
    series = pd.Series([5, 4, 3, 2, 1], index=[0, 2, 4, 6, 8])

    return series.loc[4]


print(series_loc_value())

$ python ./series/series_loc/series_loc_single_result.py
4    3
dtype: int64

With a scalar integer. Returns multiple value.¶

import numpy as np
import pandas as pd
from numba import njit


@njit
def series_loc_many_idx():
    series = pd.Series([5, 4, 3, 2, 1], index=[0, 2, 0, 6, 0])

    return series.loc[0]


print(series_loc_many_idx())

$ python ./series/series_loc/series_loc_multiple_result.py
0    5
0    3
0    1
dtype: int64

With a slice object. Returns multiple value.¶

import numpy as np
import pandas as pd
from numba import njit


@njit
def series_loc_slice():
    series = pd.Series([5, 4, 3, 2, 1])

    return series.loc[1:3]


print(series_loc_slice())

$ python ./series/series_loc/series_loc_slice.py
1    4
2    3
3    2
dtype: int64

Navigation

pandas.Series.loc¶

Limitations¶

Examples¶