ENH: A new accessor weighted_mean for DataFrame

[Zeroto521]

• closes #xxxx
• whatsnew entry

an accessor to achieve a weighted mean

    >>> import dtoolkit.accessor
    >>> import pandas as pd
    >>> df = pd.DataFrame({"a": [1, 1], "b": [2, 2], "c": [4, 4]})
    >>> df
       a  b  c
    0  1  2  4
    1  1  2  4
    >>> df.weighted_mean([0, 5, 5])
    0    3.0
    1    3.0
    dtype: float64

[codecov]

Codecov Report

Merging #688 (470bea3) into main (6f0f7a9) will increase coverage by 0.01%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main     #688      +/-   ##
==========================================
+ Coverage   99.43%   99.45%   +0.01%     
==========================================
  Files         109      110       +1     
  Lines        1418     1461      +43     
  Branches      147      160      +13     
==========================================
+ Hits         1410     1453      +43     
  Misses          2        2              
  Partials        6        6              

Impacted Files	Coverage Δ
dtoolkit/accessor/dataframe/weighted_mean.py	100.00% <100.00%> (ø)

📣 We’re building smart automated test selection to slash your CI/CD build times. Learn more