@@ -32,32 +32,32 @@ its way towards this goal.
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Here are just a few of the things that pandas does well:
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- Easy handling of [ ** missing data** ] [ missing-data ] (represented as
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- ` NaN ` , ` NA ` , or ` NaT ` ) in floating point as well as non-floating point data;
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+ ` NaN ` , ` NA ` , or ` NaT ` ) in floating point as well as non-floating point data
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- Size mutability: columns can be [ ** inserted and
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deleted** ] [ insertion-deletion ] from DataFrame and higher dimensional
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- objects;
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+ objects
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- Automatic and explicit [ ** data alignment** ] [ alignment ] : objects can
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be explicitly aligned to a set of labels, or the user can simply
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ignore the labels and let ` Series ` , ` DataFrame ` , etc. automatically
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- align the data for you in computations;
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+ align the data for you in computations
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- Powerful, flexible [ ** group by** ] [ groupby ] functionality to perform
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split-apply-combine operations on data sets, for both aggregating
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- and transforming data;
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+ and transforming data
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- Make it [ ** easy to convert** ] [ conversion ] ragged,
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differently-indexed data in other Python and NumPy data structures
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- into DataFrame objects;
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+ into DataFrame objects
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- Intelligent label-based [ ** slicing** ] [ slicing ] , [ ** fancy
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indexing** ] [ fancy-indexing ] , and [ ** subsetting** ] [ subsetting ] of
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- large data sets;
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+ large data sets
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- Intuitive [ ** merging** ] [ merging ] and [ ** joining** ] [ joining ] data
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- sets;
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+ sets
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- Flexible [ ** reshaping** ] [ reshape ] and [ ** pivoting** ] [ pivot-table ] of
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- data sets;
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+ data sets
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- [ ** Hierarchical** ] [ mi ] labeling of axes (possible to have multiple
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- labels per tick);
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+ labels per tick)
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- Robust IO tools for loading data from [ ** flat files** ] [ flat-files ]
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(CSV and delimited), [ ** Excel files** ] [ excel ] , [ ** databases** ] [ db ] ,
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- and saving/loading data from the ultrafast [ ** HDF5 format** ] [ hdfstore ] ;
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+ and saving/loading data from the ultrafast [ ** HDF5 format** ] [ hdfstore ]
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- [ ** Time series** ] [ timeseries ] -specific functionality: date range
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generation and frequency conversion, moving window statistics,
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date shifting and lagging.
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