Fix make_trace_kwargs error due to deprecated append method

[markcc309]

Very small update to core.py. Pandas has moved to 2.0, so pd.DataFrame.append is now deprecated and make_trace_kwargs throws an error.

Resolves #4025 and #4065
#4025 : concat is not a method of pd.DataFrame -- need to use pd.concat instead.
#4065: does not produce the desired output, as per example below:

import numpy as np
import pandas as pd

# Create random 3x3 dataframe
df = pd.DataFrame(
    np.random.randint(0, 10, size=(3, 3)), 
    columns=['col1', 'col2', 'col3']
)

df_1 = pd.concat([df, df.iloc[0]], axis=0)
print(df_1)

>>>      col1  col2  col3    0
0      6.0   4.0   7.0  NaN
1      4.0   6.0   8.0  NaN
2      9.0   1.0   3.0  NaN
col1   NaN   NaN   NaN  6.0
col2   NaN   NaN   NaN  4.0
col3   NaN   NaN   NaN  7.0

df_2 = pd.concat([df, pd.DataFrame(df.iloc[0]).T], axis=0)
print(df_2)

>>>    col1  col2  col3
0     6     4     7
1     4     6     8
2     9     1     3
0     6     4     7

df_2 matches the behaviour of the old append method.

Documentation PR

• I've seen the doc/README.md file
• This change runs in the current version of Plotly on PyPI and targets the doc-prod branch OR it targets the master branch
• If this PR modifies the first example in a page or adds a new one, it is a px example if at all possible
• Every new/modified example has a descriptive title and motivating sentence or paragraph
• Every new/modified example is independently runnable
• Every new/modified example is optimized for short line count and focuses on the Plotly/visualization-related aspects of the example rather than the computation required to produce the data being visualized
• Meaningful/relatable datasets are used for all new examples instead of randomly-generated data where possible
• The random seed is set if using randomly-generated data in new/modified examples
• New/modified remote datasets are loaded from https://plotly.github.io/datasets and added to https://github.com/plotly/datasets
• Large computations are avoided in the new/modified examples in favour of loading remote datasets that represent the output of such computations
• Imports are plotly.graph_objects as go / plotly.express as px / plotly.io as pio
• Data frames are always called df
• fig = <something> call is high up in each new/modified example (either px.<something> or make_subplots or go.Figure)
• Liberal use is made of fig.add_* and fig.update_* rather than go.Figure(data=..., layout=...) in every new/modified example
• Specific adders and updaters like fig.add_shape and fig.update_xaxes are used instead of big fig.update_layout calls in every new/modified example
• fig.show() is at the end of each new/modified example
• plotly.plot() and plotly.iplot() are not used in any new/modified example
• Hex codes for colors are not used in any new/modified example in favour of these nice ones

Code PR

• I have read through the contributing notes and understand the structure of the package. In particular, if my PR modifies code of plotly.graph_objects, my modifications concern the codegen files and not generated files.
• I have added tests (if submitting a new feature or correcting a bug) or
  modified existing tests.
• For a new feature, I have added documentation examples in an existing or
  new tutorial notebook (please see the doc checklist as well).
• I have added a CHANGELOG entry if fixing/changing/adding anything substantial.
• For a new feature or a change in behaviour, I have updated the relevant docstrings in the code to describe the feature or behaviour (please see the doc checklist as well).

[alexcjohnson]

Thanks @markcc309 - I included a version of this, with a test covering pandas 1 and 2, in #4190