NaN 2013-01-03 1.0 2013-01-04 3.0 2013-01-05 5.0 2013-01-06 NaN Freq: D, dtype: float64 In [65]: df.sub(s, axis='index') Out[65]: A B C D F 2013-01-01 NaN NaN NaN NaN NaN 2013-01-02 NaN NaN NaN NaN NaN 2013-01-03 can be handled simultaneously. Matching / broadcasting behavior DataFrame has the methods add(), sub(), mul(), div() and related functions radd(), rsub(), for carrying out binary operations. For broadcasting In [22]: df.sub(row, axis='columns') Out[22]: one two three a -0.889039 -0.441476 NaN b 0.000000 0.000000 0.000000 c -0.159719 -0.767122 -2.296662 d NaN -0.095880 -0.210291 In [23]: df.sub(row, axis=1)

analysis toolkit, Release 1.3.3 (continued from previous page) Freq: D, dtype: float64 In [65]: df.sub(s, axis="index") Out[65]: A B C D F 2013-01-01 NaN NaN NaN NaN NaN 2013-01-02 NaN NaN NaN NaN NaN can be handled simultaneously. Matching / broadcasting behavior DataFrame has the methods add(), sub(), mul(), div() and related functions radd(), rsub(), ... for carrying out binary operations. For broadcasting In [22]: df.sub(row, axis="columns") Out[22]: one two three a 1.051928 -0.139606 NaN b 0.000000 0.000000 0.000000 c 0.352192 -0.433754 1.277825 d NaN -1.632779 -0.562782 In [23]: df.sub(row, axis=1)

analysis toolkit, Release 1.3.4 (continued from previous page) Freq: D, dtype: float64 In [65]: df.sub(s, axis="index") Out[65]: A B C D F 2013-01-01 NaN NaN NaN NaN NaN 2013-01-02 NaN NaN NaN NaN NaN can be handled simultaneously. Matching / broadcasting behavior DataFrame has the methods add(), sub(), mul(), div() and related functions radd(), rsub(), ... for carrying out binary operations. For broadcasting In [22]: df.sub(row, axis="columns") Out[22]: one two three a 1.051928 -0.139606 NaN b 0.000000 0.000000 0.000000 c 0.352192 -0.433754 1.277825 d NaN -1.632779 -0.562782 In [23]: df.sub(row, axis=1)

2013-01-03 1.0 2013-01-04 3.0 2013-01-05 5.0 2013-01-06 NaN Freq: D, dtype: float64 In [65]: df.sub(s, axis="index") Out[65]: A B C D F 2013-01-01 NaN NaN NaN NaN NaN 2013-01-02 NaN NaN NaN NaN NaN can be handled simultaneously. Matching / broadcasting behavior DataFrame has the methods add(), sub(), mul(), div() and related functions radd(), rsub(), ... for carrying out binary operations. For broadcasting In [22]: df.sub(row, axis="columns") Out[22]: one two three a 1.051928 -0.139606 NaN b 0.000000 0.000000 0.000000 c 0.352192 -0.433754 1.277825 d NaN -1.632779 -0.562782 In [23]: df.sub(row, axis=1)

analysis toolkit, Release 1.4.2 (continued from previous page) Freq: D, dtype: float64 In [65]: df.sub(s, axis="index") Out[65]: A B C D F 2013-01-01 NaN NaN NaN NaN NaN 2013-01-02 NaN NaN NaN NaN NaN can be handled simultaneously. Matching / broadcasting behavior DataFrame has the methods add(), sub(), mul(), div() and related functions radd(), rsub(), ... for carrying out binary operations. For broadcasting In [22]: df.sub(row, axis="columns") Out[22]: one two three a 1.051928 -0.139606 NaN b 0.000000 0.000000 0.000000 c 0.352192 -0.433754 1.277825 d NaN -1.632779 -0.562782 In [23]: df.sub(row, axis=1)

analysis toolkit, Release 1.4.4 (continued from previous page) Freq: D, dtype: float64 In [65]: df.sub(s, axis="index") Out[65]: A B C D F 2013-01-01 NaN NaN NaN NaN NaN 2013-01-02 NaN NaN NaN NaN NaN can be handled simultaneously. Matching / broadcasting behavior DataFrame has the methods add(), sub(), mul(), div() and related functions radd(), rsub(), ... for carrying out binary operations. For broadcasting In [22]: df.sub(row, axis="columns") Out[22]: one two three a 1.051928 -0.139606 NaN b 0.000000 0.000000 0.000000 c 0.352192 -0.433754 1.277825 d NaN -1.632779 -0.562782 In [23]: df.sub(row, axis=1)

2013-01-03 1.0 2013-01-04 3.0 2013-01-05 5.0 2013-01-06 NaN Freq: D, dtype: float64 In [65]: df.sub(s, axis="index") Out[65]: A B C D F 2013-01-01 NaN NaN NaN NaN NaN 2013-01-02 NaN NaN NaN NaN NaN can be handled simultaneously. Matching / broadcasting behavior DataFrame has the methods add(), sub(), mul(), div() and related functions radd(), rsub(), ... for carrying out binary operations. For broadcasting In [22]: df.sub(row, axis="columns") Out[22]: one two three a 1.051928 -0.139606 NaN b 0.000000 0.000000 0.000000 c 0.352192 -0.433754 1.277825 d NaN -1.632779 -0.562782 In [23]: df.sub(row, axis=1)

Development Team is the collection of developers of the PyData project. This includes all of the PyData sub-projects, including pandas. The core team that coordinates development on GitHub can be found here: be handled simultaneously. 6.3.1 Matching / broadcasting behavior DataFrame has the methods add, sub, mul, div and related functions radd, rsub, ... for carrying out binary operations. For broadcasting In [17]: df.sub(row, axis=’columns’) Out[17]: one three two a 0.813472 NaN -1.149708 b 0.000000 0.000000 0.000000 c -0.666027 -0.146436 -1.019284 d NaN 0.577285 -0.109474 In [18]: df.sub(row, axis=1)

Development Team is the collection of developers of the PyData project. This includes all of the PyData sub-projects, including pandas. The core team that coordinates development on GitHub can be found here: be handled simultaneously. 6.3.1 Matching / broadcasting behavior DataFrame has the methods add, sub, mul, div and related functions radd, rsub, ... for carrying out binary operations. For broadcasting In [17]: df.sub(row, axis=’columns’) Out[17]: one three two a 1.791908 NaN -0.631509 b 0.000000 0.000000 0.000000 c 1.796433 0.145898 2.047038 d NaN 1.043293 -0.496764 In [18]: df.sub(row, axis=1)

Development Team is the collection of developers of the PyData project. This includes all of the PyData sub-projects, including pandas. The core team that coordinates development on GitHub can be found here: be handled simultaneously. 6.3.1 Matching / broadcasting behavior DataFrame has the methods add, sub, mul, div and related functions radd, rsub, ... for carrying out binary operations. For broadcasting In [17]: df.sub(row, axis=’columns’) Out[17]: one three two a -1.670205 NaN 0.770434 b 0.000000 0.000000 0.000000 c 1.050451 -3.231782 0.182734 d NaN -2.074872 -0.669178 In [18]: df.sub(row, axis=1)