(
df,
grouper,
key,
shuffled,
group_keys=GROUP_KEYS_DEFAULT,
dropna=None,
observed=None,
**kwargs,
)
| 149 | |
| 150 | |
| 151 | def _groupby_slice_shift( |
| 152 | df, |
| 153 | grouper, |
| 154 | key, |
| 155 | shuffled, |
| 156 | group_keys=GROUP_KEYS_DEFAULT, |
| 157 | dropna=None, |
| 158 | observed=None, |
| 159 | **kwargs, |
| 160 | ): |
| 161 | # No need to use raise if unaligned here - this is only called after |
| 162 | # shuffling, which makes everything aligned already |
| 163 | dropna = {"dropna": dropna} if dropna is not None else {} |
| 164 | observed = {"observed": observed} if observed is not None else {} |
| 165 | if shuffled: |
| 166 | df = df.sort_index() |
| 167 | g = df.groupby(grouper, group_keys=group_keys, **observed, **dropna) |
| 168 | if key: |
| 169 | g = g[key] |
| 170 | with check_groupby_axis_deprecation(): |
| 171 | result = g.shift(**kwargs) |
| 172 | return result |
| 173 | |
| 174 | |
| 175 | def _groupby_get_group(df, by_key, get_key, columns): |
no test coverage detected