CLN: deprecate/remove the pandas.tseries.plotting.tsplot function

[jorisvandenbossche]

xref #17814

As far as I can see, the tsplot function (https://github.com/pandas-dev/pandas/blob/master/pandas/plotting/_timeseries.py#L23) is not used internally, and it is not exposed in the pandas.plotting namespace (it is still exposed in pandas.tseries.plotting).
And I also don't think it is actually a useful function for users? (they would just do ts.plot(), and here you have to awkwardly provide an actual plotting function)

[starlord1311]

i would like to take up this issue. can i??

[jorisvandenbossche]

@starlord1311 Yes, sure!

[starlord1311]

@jorisvandenbossche can you tell what i am supposed to do?

[jorisvandenbossche]

You need to add a deprecation warning to the tsplot function, see eg #18258

[r-velde]

But can ts.plot use err_style? This is why I use this function, to show replicates.

[jorisvandenbossche]

@r-velde can you show a code example?

[r-velde]

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

df = pd.read_excel('TimeSeries1.xlsx', sheetname='Sheet1')

ax=sns.tsplot(time="Time (Weeks)",condition="Group",unit="Well",value="Area",data=df,err_style="unit_traces")

With the following data in excel:

Group | Well | Time | Area | Time (Weeks)
96 | 1 | 0 | 1.447972 | 0
96 | 1 | 2.066667 | 1.385389 | 0.012302
96 | 1 | 6 | 1.557112 | 0.035714
96 | 1 | 12 | 1.619833 | 0.071429
96 | 1 | 18 | 1.784649 | 0.107143
96 | 1 | 24 | 1.882875 | 0.142857
96 | 1 | 30 | 1.973433 | 0.178571
96 | 1 | 36 | 2.224801 | 0.214286
96 | 1 | 42 | 2.567142 | 0.25
96 | 1 | 48 | 2.944919 | 0.285714
96 | 1 | 54 | 3.120924 | 0.321429
96 | 1 | 60 | 3.598447 | 0.357143
96 | 1 | 66 | 3.944035 | 0.392857
96 | 1 | 72 | 4.473848 | 0.428571
96 | 1 | 78 | 4.870275 | 0.464286
96 | 1 | 84 | 5.629766 | 0.5
96 | 1 | 90 | 6.299804 | 0.535714
96 | 1 | 96 | 6.983381 | 0.571429
96 | 1 | 102 | 7.955833 | 0.607143
96 | 1 | 108 | 8.270613 | 0.642857
96 | 1 | 114 | 8.913711 | 0.678571
96 | 2 | 0 | 1.53632 | 0
96 | 2 | 2.066667 | 1.506894 | 0.012302
96 | 2 | 6 | 1.650917 | 0.035714
96 | 2 | 12 | 1.733463 | 0.071429
96 | 2 | 18 | 2.00811 | 0.107143
96 | 2 | 24 | 2.060676 | 0.142857
96 | 2 | 30 | 2.231156 | 0.178571
96 | 2 | 36 | 2.530601 | 0.214286
96 | 2 | 42 | 2.90223 | 0.25
96 | 2 | 48 | 3.294374 | 0.285714
96 | 2 | 54 | 3.632709 | 0.321429
96 | 2 | 60 | 4.240164 | 0.357143
96 | 2 | 66 | 4.674652 | 0.392857
96 | 2 | 72 | 5.282797 | 0.428571
96 | 2 | 78 | 5.963542 | 0.464286
96 | 2 | 84 | 6.635168 | 0.5
96 | 2 | 90 | 7.489432 | 0.535714
96 | 2 | 96 | 8.36504 | 0.571429
96 | 2 | 102 | 9.27712 | 0.607143
96 | 2 | 108 | 9.850797 | 0.642857
96 | 2 | 114 | 10.6833 | 0.678571

[jorisvandenbossche]

@r-velde this is tsplot from seaborn you show, not from pandas, so this issue will not impact you!

[r-velde]

@jorisvandenbossche Okay thanks.