This is up for debate: I'm only +0.2 here.The renaming was done inmatplotlib#27901, which renamed the parameter `labels`to `tick_labels` for `boxplot()` and `bxp()`.One can take two views here:- If `boxplot_stats()` is specifically for the input of `bxp()`, one  can justify the renaming as being consistent with the `bxp()`  signature. Note however, that the returned dict still  contains the key "label" for back-compatibility. So that brings us  an inconsistency between the parameter name and the returned dict key.- One can alternatively view `boxplot_stats()` as a generic function to  define box parameters. Here, we'd only have a general `label` for  the boy and no information that this should be used as tick  label.If we could make a clean transition and also rename the dict key, Iwould tend to go with the first view. But the inevitable inconsistencyof the fist view let's me sway towards the second view, so that withthe revert, we've effectively not touched `boxplot_stats()`.

This is up for debate: I'm only +0.2 here.The renaming was done inmatplotlib#27901, which renamed the parameter `labels`to `tick_labels` for `boxplot()` and `bxp()`.One can take two views here:- If `boxplot_stats()` is specifically for the input of `bxp()`, one  can justify the renaming as being consistent with the `bxp()`  signature. Note however, that the returned dict still  contains the key "label" for back-compatibility. So that brings us  an inconsistency between the parameter name and the returned dict key.- One can alternatively view `boxplot_stats()` as a generic function to  define box parameters. Here, we'd only have a general `label` for  the boy and no information that this should be used as tick  label.If we could make a clean transition and also rename the dict key, Iwould tend to go with the first view. But the inevitable inconsistencyof the fist view let's me sway towards the second view, so that withthe revert, we've effectively not touched `boxplot_stats()`.

This is up for debate: I'm only +0.2 here.The renaming was done inmatplotlib#27901, which renamed the parameter `labels`to `tick_labels` for `boxplot()` and `bxp()`.One can take two views here:- If `boxplot_stats()` is specifically for the input of `bxp()`, one  can justify the renaming as being consistent with the `bxp()`  signature. Note however, that the returned dict still  contains the key "label" for back-compatibility. So that brings us  an inconsistency between the parameter name and the returned dict key.- One can alternatively view `boxplot_stats()` as a generic function to  define box parameters. Here, we'd only have a general `label` for  the boy and no information that this should be used as tick  label.If we could make a clean transition and also rename the dict key, Iwould tend to go with the first view. But the inevitable inconsistencyof the fist view let's me sway towards the second view, so that withthe revert, we've effectively not touched `boxplot_stats()`.

This is up for debate: I'm only +0.2 here.The renaming was done inmatplotlib#27901, which renamed the parameter `labels`to `tick_labels` for `boxplot()` and `bxp()`.One can take two views here:- If `boxplot_stats()` is specifically for the input of `bxp()`, one  can justify the renaming as being consistent with the `bxp()`  signature. Note however, that the returned dict still  contains the key "label" for back-compatibility. So that brings us  an inconsistency between the parameter name and the returned dict key.- One can alternatively view `boxplot_stats()` as a generic function to  define box parameters. Here, we'd only have a general `label` for  the boy and no information that this should be used as tick  label.If we could make a clean transition and also rename the dict key, Iwould tend to go with the first view. But the inevitable inconsistencyof the fist view let's me sway towards the second view, so that withthe revert, we've effectively not touched `boxplot_stats()`.