Update Woodwork to 0.0.10

[angela97lin]

Closes #1899

Changes made in 0.0.10 to mutual_information (alteryx/woodwork#563) s.t. columns which have completely unique values are no longer considered. Hence, had to tweak some of our tests so that the return values were as expected.

[codecov]

Codecov Report

Merging #1900 (bbf68e7) into main (7b400c8) will not change coverage.
The diff coverage is 100.0%.

@@           Coverage Diff           @@
##             main    #1900   +/-   ##
=======================================
  Coverage   100.0%   100.0%           
=======================================
  Files         263      263           
  Lines       21300    21299    -1     
=======================================
- Hits        21294    21293    -1     
  Misses          6        6           

Impacted Files	Coverage Δ
evalml/data_checks/target_leakage_data_check.py	100.0% <ø> (ø)
evalml/tests/data_checks_tests/test_data_checks.py	100.0% <100.0%> (ø)
..._checks_tests/test_multicollinearity_data_check.py	100.0% <100.0%> (ø)
...ata_checks_tests/test_target_leakage_data_check.py	100.0% <100.0%> (ø)

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[bchen1116]

LGTM

[freddyaboulton]

I saw your comment about how woodwork will not calculate mutual information if one of the columns has all unique values. I guess that means that the mutual information is 0 in that case.

Does this mean we should update the DefaultDataChecks to use method='pearson' for regression? Columns can still be 95% correlated with the target if the target is all unique.