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lines changed Original file line number Diff line number Diff line change @@ -9038,16 +9038,6 @@ def combine(
90389038 0 0 -5.0
90399039 1 0 4.0
90409040
9041- However, if the same element in both dataframes is None, that None
9042- is preserved
9043-
9044- >>> df1 = pd.DataFrame({"A": [0, 0], "B": [None, 4]})
9045- >>> df2 = pd.DataFrame({"A": [1, 1], "B": [None, 3]})
9046- >>> df1.combine(df2, take_smaller, fill_value=-5)
9047- A B
9048- 0 0 -5.0
9049- 1 0 3.0
9050-
90519041 Example that demonstrates the use of `overwrite` and behavior when
90529042 the axis differ between the dataframes.
90539043
@@ -13820,8 +13810,8 @@ def quantile(
1382013810 0.1 1 1
1382113811 0.5 3 100
1382213812
13823- Specifying `numeric_only=False` will also compute the quantile of
13824- datetime and timedelta data .
13813+ Specifying `numeric_only=False` will compute the quantiles for all
13814+ columns .
1382513815
1382613816 >>> df = pd.DataFrame(
1382713817 ... {
Original file line number Diff line number Diff line change @@ -3112,8 +3112,8 @@ def combine(
31123112
31133113 Combine the Series and `other` using `func` to perform elementwise
31143114 selection for combined Series.
3115- `fill_value` is assumed when value is missing at some index
3116- from one of the two objects being combined.
3115+ `fill_value` is assumed when value is not present at some index
3116+ from one of the two Series being combined.
31173117
31183118 Parameters
31193119 ----------
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