pandas: powerful Python data analysis toolkit - 0.12C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3 Release 0.12.0 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g30 码力 | 657 页 | 3.58 MB | 1 年前3- pandas: powerful Python data analysis toolkit - 1.3.2C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3 C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 from_product([['A', 'B'], ['r1', 'r2']]), columns=['c1','c2','c3','c4']) df3 [29]: c1 c2 c3 c4 A r1 -1.048553 -1.420018 -1.706270 1.950775 r2 -0.509652 -0.438074 -1.252795 0.777490 B r1 -1.613898 -0.212740 -00 码力 | 3509 页 | 14.01 MB | 1 年前3
- pandas: powerful Python data analysis toolkit - 1.3.3C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3 C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 from_product([['A', 'B'], ['r1', 'r2']]), columns=['c1','c2','c3','c4']) df3 [29]: c1 c2 c3 c4 A r1 -1.048553 -1.420018 -1.706270 1.950775 r2 -0.509652 -0.438074 -1.252795 0.777490 B r1 -1.613898 -0.212740 -00 码力 | 3603 页 | 14.65 MB | 1 年前3
- pandas: powerful Python data analysis toolkit - 1.3.4C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3 C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 from_product([['A', 'B'], ['r1', 'r2']]), columns=['c1','c2','c3','c4']) df3 [29]: c1 c2 c3 c4 A r1 -1.048553 -1.420018 -1.706270 1.950775 r2 -0.509652 -0.438074 -1.252795 0.777490 B r1 -1.613898 -0.212740 -00 码力 | 3605 页 | 14.68 MB | 1 年前3
- pandas: powerful Python data analysis toolkit - 1.4.2C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 (continues on next page) 306 Chapter C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 from_product([['A', 'B'], ['r1', 'r2']]), columns=['c1','c2','c3','c4']) df3 [33]: c1 c2 c3 c4 A r1 -1.048553 -1.420018 -1.706270 1.950775 r2 -0.509652 -0.438074 -1.252795 0.777490 B r1 -1.613898 -0.212740 -00 码力 | 3739 页 | 15.24 MB | 1 年前3
- pandas: powerful Python data analysis toolkit - 1.4.4C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3 C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 from_product([['A', 'B'], ['r1', 'r2']]), columns=['c1','c2','c3','c4']) df3 [33]: c1 c2 c3 c4 A r1 -1.048553 -1.420018 -1.706270 1.950775 r2 -0.509652 -0.438074 -1.252795 0.777490 B r1 -1.613898 -0.212740 -00 码力 | 3743 页 | 15.26 MB | 1 年前3
- pandas: powerful Python data analysis toolkit - 0.13.1C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3 C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g30 码力 | 1219 页 | 4.81 MB | 1 年前3
- pandas: powerful Python data analysis toolkit - 1.5.0rc0C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 (continues on next page) 2.2. Guides 311 pandas: powerful Python C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 from_product([['A', 'B'], ['r1', 'r2']]), columns=['c1','c2','c3','c4']) df3 [33]: c1 c2 c3 c4 A r1 -1.048553 -1.420018 -1.706270 1.950775 r2 -0.509652 -0.438074 -1.252795 0.777490 B r1 -1.613898 -0.212740 -00 码力 | 3943 页 | 15.73 MB | 1 年前3
- pandas: powerful Python data analysis toolkit - 0.14.0C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3 C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g3 Python data analysis toolkit, Release 0.14.0 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g30 码力 | 1349 页 | 7.67 MB | 1 年前3
- pandas: powerful Python data analysis toolkit - 0.25C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3 C_l0_g1 C_l0_g2 C1 C_l1_g0 C_l1_g1 C_l1_g2 C2 C_l2_g0 C_l2_g1 C_l2_g2 C3 C_l3_g0 C_l3_g1 C_l3_g2 R0 R1 R_l0_g0 R_l1_g0 R0C0 R0C1 R0C2 R_l0_g1 R_l1_g1 R1C0 R1C1 R1C2 R_l0_g2 R_l1_g2 R2C0 R2C1 R2C2 R_l0_g30 码力 | 698 页 | 4.91 MB | 1 年前3
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