pandas: powerful Python data analysis toolkit - 0.7.1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 6.4 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 6.5 Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 8.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 8.3 Exponentially (1-dimensional) and DataFrame (2-dimensional), handle the vast majority of typical use cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that0 码力 | 281 页 | 1.45 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.7.2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 6.4 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 6.5 Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 8.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 8.3 Exponentially (1-dimensional) and DataFrame (2-dimensional), handle the vast majority of typical use cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that0 码力 | 283 页 | 1.45 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.7.3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 6.4 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 6.5 Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 8.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 8.3 Exponentially (1-dimensional) and DataFrame (2-dimensional), handle the vast majority of typical use cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that0 码力 | 297 页 | 1.92 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.12. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 8.5 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 8.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 10.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 10.3 Expanding (1-dimensional) and DataFrame (2-dimensional), handle the vast majority of typical use cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that0 码力 | 657 页 | 3.58 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.14.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 9.5 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 9.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 11.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 11.3 Expanding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 622 25 Pandas Ecosystem 623 25.1 Statistics and Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .0 码力 | 1349 页 | 7.67 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 9.5 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 9.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 14.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403 14.3 Expanding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 772 29 pandas Ecosystem 773 29.1 Statistics and Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .0 码力 | 1579 页 | 9.15 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15.1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 9.5 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 9.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 14.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 14.3 Expanding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 758 29 pandas Ecosystem 759 29.1 Statistics and Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .0 码力 | 1557 页 | 9.10 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.13.1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 9.5 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 9.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 11.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289 11.3 Expanding (1-dimensional) and DataFrame (2-dimensional), handle the vast majority of typical use cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that0 码力 | 1219 页 | 4.81 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.17.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 10.5 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 10.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 15.2 Moving (rolling) statistics / moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 15.3 Expanding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 895 30 pandas Ecosystem 897 30.1 Statistics and Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .0 码力 | 1787 页 | 10.76 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.1.1operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 2.3.5 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 2.3.6 Function columns is straightforward. To introduction tutorial To user guide Straight to tutorial... Basic statistics (mean, median, min, max, counts...) are easily calculable. These or custom aggregations can be read_html (see note) matplotlib 2.2.2 Visualization numba 0.46.0 Alternative execution engine for rolling operations openpyxl 2.5.7 Reading / writing for xlsx files pandas-gbq 0.12.0 Google Big Query access0 码力 | 3231 页 | 10.87 MB | 1 年前3
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