DEPR: tz_convert in the Timestamp constructor
State: closed

- [x] closes #23579
- [x] tests added / passed
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry

To have consistent behavior with `DatetimeIndex`, deprecate the `tz_convert` behavior of the `Timestamp` constructor with the `tz` arg.

Labels:
name: Datetime
description: Datetime data dtype
name: Timezones
description: Timezone data dtype
name: Deprecate
description: Functionality to remove in pandas

Comments:
Hello @mroeschke! Thanks for submitting the PR.

 - There are no PEP8 issues in the file [`pandas/tests/scalar/timestamp/test_timestamp.py`](https://github.com/mroeschke/pandas/blob/2d138089fe1f677feddd5038837b0fc9d96fe366/pandas/tests/scalar/timestamp/test_timestamp.py) !


# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/23621?src=pr&el=h1) Report
> Merging [#23621](https://codecov.io/gh/pandas-dev/pandas/pull/23621?src=pr&el=desc) into [master](https://codecov.io/gh/pandas-dev/pandas/commit/24bce1a5fdd70a66b9fb5e2f9f51631d1df6add3?src=pr&el=desc) will **increase** coverage by `<.01%`.
> The diff coverage is `96.15%`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/23621/graphs/tree.svg?width=650&token=eZ4WkYLtcO&height=150&src=pr)](https://codecov.io/gh/pandas-dev/pandas/pull/23621?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master   #23621      +/-   ##
==========================================
+ Coverage   92.23%   92.23%   +<.01%     
==========================================
  Files         161      161              
  Lines       51408    51427      +19     
==========================================
+ Hits        47416    47434      +18     
- Misses       3992     3993       +1
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `90.62% <96.15%> (ø)` | :arrow_up: |
| #single | `42.29% <23.07%> (-0.01%)` | :arrow_down: |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/23621?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/indexes/datetimes.py](https://codecov.io/gh/pandas-dev/pandas/pull/23621/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvaW5kZXhlcy9kYXRldGltZXMucHk=) | `96.2% <100%> (+0.05%)` | :arrow_up: |
| [pandas/core/arrays/datetimes.py](https://codecov.io/gh/pandas-dev/pandas/pull/23621/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvYXJyYXlzL2RhdGV0aW1lcy5weQ==) | `98.49% <100%> (ø)` | :arrow_up: |
| [pandas/core/generic.py](https://codecov.io/gh/pandas-dev/pandas/pull/23621/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZ2VuZXJpYy5weQ==) | `96.83% <100%> (ø)` | :arrow_up: |
| [pandas/io/formats/format.py](https://codecov.io/gh/pandas-dev/pandas/pull/23621/diff?src=pr&el=tree#diff-cGFuZGFzL2lvL2Zvcm1hdHMvZm9ybWF0LnB5) | `97.76% <66.66%> (-0.12%)` | :arrow_down: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/23621?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/23621?src=pr&el=footer). Last update [24bce1a...fa0e39b](https://codecov.io/gh/pandas-dev/pandas/pull/23621?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).

lgtm. can you add to the deprecations list, issue #6581 

can you replicate your tests on Timestamp on DTI (if they already exist can you xref that test with this issue / PR number)

not sure what is failing.
can you rebase, looks fine.
can you run some asvs to see if we have perf issues
No regressions according to the asvs.
```
asv continuous -f 1.1 upstream/master HEAD -b ^timestamp
· Creating environments
· Discovering benchmarks
·· Uninstalling from conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
·· Building aaec0192 for conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.......................................
·· Installing into conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt..
· Running 54 total benchmarks (2 commits * 1 environments * 27 benchmarks)
[  0.00%] · For pandas commit hash aaec0192:
[  0.00%] ·· Building for conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt...
[  0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[  0.00%] ··· Running benchmarks.............................
[  1.85%] ··· timestamp.TimestampAcrossDst.time_replace_across_dst                                      18.7±0.4μs
[  3.70%] ··· timestamp.TimestampConstruction.time_fromordinal                                         1.48±0.03μs
[  5.56%] ··· timestamp.TimestampConstruction.time_fromtimestamp                                       1.72±0.03μs
[  7.41%] ··· timestamp.TimestampConstruction.time_parse_dateutil                                          110±2μs
[  9.26%] ··· timestamp.TimestampConstruction.time_parse_iso8601_no_tz                                 1.78±0.03μs
[ 11.11%] ··· timestamp.TimestampConstruction.time_parse_iso8601_tz                                     15.4±0.6μs
[ 12.96%] ··· timestamp.TimestampConstruction.time_parse_now                                           2.13±0.05μs
[ 14.81%] ··· timestamp.TimestampConstruction.time_parse_today                                         2.18±0.05μs
[ 16.67%] ··· timestamp.TimestampOps.time_replace_None                                             1.89±0.04μs;...
[ 18.52%] ··· timestamp.TimestampOps.time_replace_tz                                               21.0±0.09μs;...
[ 20.37%] ··· timestamp.TimestampOps.time_to_pydatetime                                                584±8ns;...
[ 22.22%] ··· timestamp.TimestampProperties.time_dayofweek                                             271±3ns;...
[ 24.07%] ··· timestamp.TimestampProperties.time_dayofyear                                            337±30ns;...
[ 25.93%] ··· timestamp.TimestampProperties.time_days_in_month                                         287±5ns;...
[ 27.78%] ··· timestamp.TimestampProperties.time_freqstr                                               494±9ns;...
[ 29.63%] ··· timestamp.TimestampProperties.time_is_leap_year                                          272±2ns;...
[ 31.48%] ··· timestamp.TimestampProperties.time_is_month_end                                         380±30ns;...
[ 33.33%] ··· timestamp.TimestampProperties.time_is_month_start                                        270±6ns;...
[ 35.19%] ··· timestamp.TimestampProperties.time_is_quarter_end                                       283±10ns;...
[ 37.04%] ··· timestamp.TimestampProperties.time_is_quarter_start                                      274±6ns;...
[ 38.89%] ··· timestamp.TimestampProperties.time_is_year_end                                           283±4ns;...
[ 40.74%] ··· timestamp.TimestampProperties.time_is_year_start                                         268±1ns;...
[ 42.59%] ··· timestamp.TimestampProperties.time_microsecond                                           214±1ns;...
[ 44.44%] ··· timestamp.TimestampProperties.time_quarter                                               264±6ns;...
[ 46.30%] ··· timestamp.TimestampProperties.time_tz                                                    242±2ns;...
[ 48.15%] ··· timestamp.TimestampProperties.time_week                                                  320±8ns;...
[ 50.00%] ··· timestamp.TimestampProperties.time_weekday_name                                       9.87±0.7μs;...
[ 50.00%] · For pandas commit hash db2066b7:
[ 50.00%] ·· Building for conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt..........................................
[ 50.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 50.00%] ··· Running benchmarks.............................
[ 51.85%] ··· timestamp.TimestampAcrossDst.time_replace_across_dst                                        21.3±2μs
[ 53.70%] ··· timestamp.TimestampConstruction.time_fromordinal                                          1.70±0.3μs
[ 55.56%] ··· timestamp.TimestampConstruction.time_fromtimestamp                                        1.84±0.2μs
[ 57.41%] ··· timestamp.TimestampConstruction.time_parse_dateutil                                          110±4μs
[ 59.26%] ··· timestamp.TimestampConstruction.time_parse_iso8601_no_tz                                 1.54±0.04μs
[ 61.11%] ··· timestamp.TimestampConstruction.time_parse_iso8601_tz                                     15.1±0.3μs
[ 62.96%] ··· timestamp.TimestampConstruction.time_parse_now                                           1.92±0.07μs
[ 64.81%] ··· timestamp.TimestampConstruction.time_parse_today                                         1.92±0.02μs
[ 66.67%] ··· timestamp.TimestampOps.time_replace_None                                             2.05±0.06μs;...
[ 68.52%] ··· timestamp.TimestampOps.time_replace_tz                                                20.7±0.2μs;...
[ 70.37%] ··· timestamp.TimestampOps.time_to_pydatetime                                               601±30ns;...
[ 72.22%] ··· timestamp.TimestampProperties.time_dayofweek                                             266±6ns;...
[ 74.07%] ··· timestamp.TimestampProperties.time_dayofyear                                             305±5ns;...
[ 75.93%] ··· timestamp.TimestampProperties.time_days_in_month                                         284±9ns;...
[ 77.78%] ··· timestamp.TimestampProperties.time_freqstr                                              508±10ns;...
[ 79.63%] ··· timestamp.TimestampProperties.time_is_leap_year                                          291±9ns;...
[ 81.48%] ··· timestamp.TimestampProperties.time_is_month_end                                         369±10ns;...
[ 83.33%] ··· timestamp.TimestampProperties.time_is_month_start                                        288±6ns;...
[ 85.19%] ··· timestamp.TimestampProperties.time_is_quarter_end                                       290±20ns;...
[ 87.04%] ··· timestamp.TimestampProperties.time_is_quarter_start                                      277±4ns;...
[ 88.89%] ··· timestamp.TimestampProperties.time_is_year_end                                          279±10ns;...
[ 90.74%] ··· timestamp.TimestampProperties.time_is_year_start                                         277±5ns;...
[ 92.59%] ··· timestamp.TimestampProperties.time_microsecond                                          233±10ns;...
[ 94.44%] ··· timestamp.TimestampProperties.time_quarter                                               269±6ns;...
[ 96.30%] ··· timestamp.TimestampProperties.time_tz                                                    242±4ns;...
[ 98.15%] ··· timestamp.TimestampProperties.time_week                                                 320±10ns;...
[100.00%] ··· timestamp.TimestampProperties.time_weekday_name                                       9.57±0.5μs;...

BENCHMARKS NOT SIGNIFICANTLY CHANGED.
```
thanks @mroeschke