Question

我正在关注Lynda教程，他们使用以下代码：

index.html

它完美无缺。但是，在我的情况下，似乎代码没有编译，对于最后一行我一直收到错误。

TypeError：无法将项目插入尚未成为现有类别的CategoricalIndex

我在视频中知道他们使用的是Python 2，但是因为我正在学习工作（使用Python 3），所以我有Python 3。我已经能够弄清楚大多数差异，但是我无法弄清楚如何用乘客的总和来创建这个名为import pandas as pd import seaborn flights = seaborn.load_dataset('flights') flights_indexed = flights.set_index(['year','month']) flights_unstacked = flights_indexed.unstack() flights_unstacked['passengers','total'] = flights_unstacked.sum(axis=1)的新列。

Answer 1

此错误消息的根本原因是month列的分类性质：

In [42]: flights.dtypes
Out[42]:
year             int64
month         category
passengers       int64
dtype: object

 In [43]: flights.month.cat.categories
Out[43]: Index(['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December'], d
type='object')

并且您正在尝试添加类别total - Pandas不喜欢这样。

解决方法：

In [45]: flights.month.cat.add_categories('total', inplace=True) In [46]: x = flights.pivot(index='year', columns='month', values='passengers') In [47]: x['total'] = x.sum(1) In [48]: x Out[48]: month January February March April May June July August September October November December total year 1949 112.0 118.0 132.0 129.0 121.0 135.0 148.0 148.0 136.0 119.0 104.0 118.0 1520.0 1950 115.0 126.0 141.0 135.0 125.0 149.0 170.0 170.0 158.0 133.0 114.0 140.0 1676.0 1951 145.0 150.0 178.0 163.0 172.0 178.0 199.0 199.0 184.0 162.0 146.0 166.0 2042.0 1952 171.0 180.0 193.0 181.0 183.0 218.0 230.0 242.0 209.0 191.0 172.0 194.0 2364.0 1953 196.0 196.0 236.0 235.0 229.0 243.0 264.0 272.0 237.0 211.0 180.0 201.0 2700.0 1954 204.0 188.0 235.0 227.0 234.0 264.0 302.0 293.0 259.0 229.0 203.0 229.0 2867.0 1955 242.0 233.0 267.0 269.0 270.0 315.0 364.0 347.0 312.0 274.0 237.0 278.0 3408.0 1956 284.0 277.0 317.0 313.0 318.0 374.0 413.0 405.0 355.0 306.0 271.0 306.0 3939.0 1957 315.0 301.0 356.0 348.0 355.0 422.0 465.0 467.0 404.0 347.0 305.0 336.0 4421.0 1958 340.0 318.0 362.0 348.0 363.0 435.0 491.0 505.0 404.0 359.0 310.0 337.0 4572.0 1959 360.0 342.0 406.0 396.0 420.0 472.0 548.0 559.0 463.0 407.0 362.0 405.0 5140.0 1960 417.0 391.0 419.0 461.0 472.0 535.0 622.0 606.0 508.0 461.0 390.0 432.0 5714.0

更新：或者，如果您不想触摸原始DF，则可以删除flights_unstacked DF中的分类列：

In [76]: flights_unstacked.columns = \ ...: flights_unstacked.columns \ ...: .set_levels(flights_unstacked.columns.get_level_values(1).categories, ...: level=1) ...: In [77]: flights_unstacked['passengers','total'] = flights_unstacked.sum(axis=1) In [78]: flights_unstacked Out[78]: passengers month January February March April May June July August September October November December total year 1949 112 118 132 129 121 135 148 148 136 119 104 118 1520 1950 115 126 141 135 125 149 170 170 158 133 114 140 1676 1951 145 150 178 163 172 178 199 199 184 162 146 166 2042 1952 171 180 193 181 183 218 230 242 209 191 172 194 2364 1953 196 196 236 235 229 243 264 272 237 211 180 201 2700 1954 204 188 235 227 234 264 302 293 259 229 203 229 2867 1955 242 233 267 269 270 315 364 347 312 274 237 278 3408 1956 284 277 317 313 318 374 413 405 355 306 271 306 3939 1957 315 301 356 348 355 422 465 467 404 347 305 336 4421 1958 340 318 362 348 363 435 491 505 404 359 310 337 4572 1959 360 342 406 396 420 472 548 559 463 407 362 405 5140 1960 417 391 419 461 472 535 622 606 508 461 390 432 5714

Python Pandas Dataframe赋值

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