pandas: powerful Python data analysis toolkit - 0.25at[dates[0], 'A'] Out[31]: 1.8327469709663295 Selection by position See more in Selection by Position. Select via the position of the passed integers: In [32]: df.iloc[3] Out[32]: A 0.509859 B -2.769586 C [38]: df.iat[1, 1] Out[38]: 0.03514142900432859 Boolean indexing Using a single columns values to select data. In [39]: df[df.A > 0] Out[39]: A B C D 2013-01-01 1.832747 1.515386 1.793547 -0.360634 630194 0.673233 0.693157 0.744467 0.762700 max 3.210008 2.340774 3.014330 3.111480 2.846670 You can select specific percentiles to include in the output: In [99]: series.describe(percentiles=[.05, .25,0 码力 | 698 页 | 4.91 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 12.16 The select() Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 784 31 Comparison with SQL 789 31.1 SELECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . variables exported to Stata data files. • Added flag order_categoricals to StataReader and read_stata to select whether to order im- ported categorical data (GH8836). See here for more information on importing0 码力 | 1579 页 | 9.15 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15.1get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358 12.16 The select() Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359 12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 770 31 Comparison with SQL 775 31.1 SELECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Index properties is_monotonic_increasing and is_monotonic_decreasing (GH8680). • Added option to select columns when importing Stata files (GH7935) • Qualify memory usage in DataFrame.info() by adding0 码力 | 1557 页 | 9.10 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.17.0get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443 13.16 The select() Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443 13 . . . . . . . . . . . . . . . . . . . . . . . . . . . 908 vi 32 Comparison with SQL 913 32.1 SELECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . to not respect the axis parameter when the frame has a symmetric shape. (GH9736) • Bug in Table.select_column where name is not preserved (GH10392) • Bug in offsets.generate_range where start and end0 码力 | 1787 页 | 10.76 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.14.0with .ix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 10.17 The select() Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286 10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 632 v 27 Comparison with SQL 637 27.1 SELECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . doesn’t make sense NotImplementedError: operator ’/’ not implemented for bool dtypes • In HDFStore, select_as_multiple will always raise a KeyError, when a key or the selector is not found (GH6177) • df[’col’]0 码力 | 1349 页 | 7.67 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.13.1with .ix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 10.17 The select() Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260 10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 570 27 Comparison with SQL 575 27.1 SELECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 065587 8 -0.092759 9 1.391365 dtype: float64 • query() method has been added that allows you to select elements of a DataFrame using a natural query syntax nearly identical to Python syntax. For example0 码力 | 1219 页 | 4.81 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.12(ie, matplotlib.cm.jet) or a string name of such an object (ie, ‘jet’). The colormap is sampled to select the color for each column. Please see Colormaps for more information. (GH3860) • DataFrame.interpolate() (GH3275) • HDFStore – added the method select_column to select a single column from a table as a Series. – deprecated the unique method, can be replicated by select_column(key,column).unique() – min_itemsize port iteration on select and select_as_multiple (GH3076) • You can now select timestamps from an unordered timeseries similarly to an ordered timeseries (GH2437) • You can now select with a string from0 码力 | 657 页 | 3.58 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.19.0get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 562 13.17 The select() Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 562 13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1062 33 Comparison with SQL 1065 33.1 SELECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1114 pandas.HDFStore.select . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1115 35.1.8 SAS . . .0 码力 | 1937 页 | 12.03 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.19.1get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564 13.17 The select() Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564 13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1064 33 Comparison with SQL 1067 33.1 SELECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1117 pandas.HDFStore.select . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1117 35.1.8 SAS . . .0 码力 | 1943 页 | 12.06 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.20.3get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625 12.18 The select() Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 626 12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1156 32 Comparison with SQL 1159 32.1 SELECT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1214 34.1.7.5 pandas.HDFStore.select . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1214 34.1.8 Feather . . . . . .0 码力 | 2045 页 | 9.18 MB | 1 年前3
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