4 Credits 24 4.5 Development Team 24 4.6 License 24 5 Intro to Data Structures 27 5.1 Series 27 5.2 DataFrame 31 5.3 Panel 44 6 Essential basic functionality 49 6.1 Head and Tail cross-tabulations ..... 161 13 Time Series / Date functionality ..... 165 13.1 DateOffset objects ..... 165 13.2 Generating date ranges (DateRange) ..... 167 13.3 Time series-related instance methods .. plyr 209 20.5 reshape / reshape2 209 21 API Reference 211 21.1 General functions 211 21.2 Series 226 21.3 DataFrame 248 21.4 Panel 284 Python Module Index 285 Python Module Index 287

4 Credits 20 4.5 Development Team 20 4.6 License 20 5 Intro to Data Structures 23 5.1 Series 23 5.2 DataFrame 27 5.3 Panel 40 6 Essential basic functionality 43 6.1 Head and Tail cross-tabulations ..... 153 13 Time Series / Date functionality ..... 157 13.1 DateOffset objects ..... 157 13.2 Generating date ranges (DateRange) ..... 159 13.3 Time series-related instance methods .. plyr 197 20.5 reshape / reshape2 197 21 API Reference 199 21.1 General functions 199 21.2 Series 214 21.3 DataFrame 236 21.4 Panel 269 Python Module Index 271 Python Module Index 273

(October 2, 2016) 3 1.1.1 New features 5 merge_asof for asof-style time-series joining 5 .rolling() is now time-series aware 7 read_csv has improved support for duplicate column names 9 Other enhancements 15 1.1.2 API changes 18 Series.tolist() will now return Python types 18 Series operators for different indexes 18 Series type promotion on assignment 21 .to_datetime() 10.3 Bug Fixes 163 1.11 v0.15.0 (October 18, 2014) 164 1.11.1 New features 165 Categoricals in Series/DataFrame 165 TimedeltaIndex/Scalar 166 Memory Usage 169 .dt accessor 170 Timezone handling improvements

4 Credits 20 4.5 Development Team 20 4.6 License 20 5 Intro to Data Structures 23 5.1 Series 23 5.2 DataFrame 27 5.3 Panel 40 6 Essential basic functionality 43 6.1 Head and Tail cross-tabulations ..... 153 13 Time Series / Date functionality ..... 157 13.1 DateOffset objects ..... 157 13.2 Generating date ranges (DateRange) ..... 159 13.3 Time series-related instance methods .. reshape / reshape2 ..... 197 21 API Reference ..... 199 21.1 General functions ..... 199 21.2 Series ..... 214 21.3 DataFrame ..... 236 21.4 Panel ..... 268 Python Module Index ..... 269

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 2.1.9 Time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 2.1.10 structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 2.2.1 Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 2 . . . . . . . . . . . . . . . . . . . . . . . . . . 508 2.7.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 518 2.7.3 Timeseries friendly merging . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 5.9 Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 8 Intro to Data Structures 147 8.1 Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374 16 Time Series / Date functionality 377 16.1 Time Stamps vs. Time Spans . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 2.1.9 Time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 2.1.10 structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 2.2.1 Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 2 . . . . . . . . . . . . . . . . . . . . . . . . . . 505 2.7.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 519 2.7.3 Timeseries friendly merging . . . .

behaviour of pd.NA can still change without warning. For example, creating a Series using the nullable integer dtype: In [3]: s = pd.Series([1, 2, None], dtype="Int64") In [4]: s Out[4]: 0 1 1 2 2 Length: string. In [9]: pd.Series(['abc', None, 'def'], dtype=pd.StringDtype()) Out[9]: 0 abc 1 2 def Length: 3, dtype: string You can use the alias "string" as well. In [10]: s = pd.Series(['abc', None, 'def'] dtype: string The usual string accessor methods work. Where appropriate, the return type of the Series or columns of a DataFrame will also have string dtype. In [12]: s.str.upper() Out[12]: 0 ABC (continues

Operations ..... 189 5.6 Merge ..... 192 5.7 Grouping ..... 194 5.8 Reshaping ..... 195 5.9 Time Series ..... 197 5.10 Categoricals ..... 198 5.11 Plotting ..... 200 5.12 Getting Data In/Out ... ..... 234 7.13 Creating Example Data ..... 235 8 Intro to Data Structures ..... 237 8.1 Series ..... 237 8.2 DataFrame ..... 242 8.3 Panel ..... 254 8.4 Panel4D (Experimental) ..... 258 18.7 Computing indicator / dummy variables ..... 487 18.8 Factorizing values ..... 490 19 Time Series / Date functionality ..... 491 19.1 Time Stamps vs. Time Spans ..... 492 19.2 Converting to Timestamps

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 2.1.9 Time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 2.1.10 structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 2.2.1 Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 2 . . . . . . . . . . . . . . . . . . . . . . . . . . 505 2.7.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 519 2.7.3 Timeseries friendly merging . . . .