Question

我正在处理与两个不同关键字相关的Twitter数据。我想计算每个关键字每天的推文数量，在折线图中可视化结果，然后将其与一系列重要日历的日期重叠事件。

我的目的是查看有关特定事件的推文计数是否发生变化。我已经计算并可视化了这些推文，但是在弄清楚如何覆盖关键日期时遇到了问题。

我尝试将重要的日期放入列表中，但是这引发了错误。谁能给我一些指导或建议一种更好的方法来解决这个问题？

这是一张图像，它大致说明了我要实现的目标： https://imgur.com/a/36esk1B

dates_list = ['2016-06-16','2016-06-23', '2016-06-24',
             '2016-07-02', '2016-07-13']

#then convert list into a Series

key_dates = pd.Series(pd.to_datetime(dates_list))

# add columns to identify important events, and mark a 0 or 1.
tweet_trend['Important Events'] = False
tweet_trend.loc[key_dates, 'Important Events'] = True
tweet_trend['values'] = 0
tweet_trend.loc[key_dates, 'values'] = 1

KeyError                                  Traceback (most recent call last)
<ipython-input-88-04dd081adc28> in <module>
     10 # add columns to identify important events, and mark a 0 or 1.
     11 tweet_trend['Important Events'] = False
---> 12 tweet_trend.loc[key_dates, 'Important Events'] = True
     13 tweet_trend['values'] = 0
     14 tweet_trend.loc[key_dates, 'values'] = 1

~/venv/lib/python3.6/site-packages/pandas/core/indexing.py in __setitem__(self, key, value)
    187         else:
    188             key = com.apply_if_callable(key, self.obj)
--> 189         indexer = self._get_setitem_indexer(key)
    190         self._setitem_with_indexer(indexer, value)
    191 

~/venv/lib/python3.6/site-packages/pandas/core/indexing.py in _get_setitem_indexer(self, key)
    165         if isinstance(key, tuple):
    166             try:
--> 167                 return self._convert_tuple(key, is_setter=True)
    168             except IndexingError:
    169                 pass

~/venv/lib/python3.6/site-packages/pandas/core/indexing.py in _convert_tuple(self, key, is_setter)
    246                 if i >= self.obj.ndim:
    247                     raise IndexingError('Too many indexers')
--> 248                 idx = self._convert_to_indexer(k, axis=i, is_setter=is_setter)
    249                 keyidx.append(idx)
    250         return tuple(keyidx)

~/venv/lib/python3.6/site-packages/pandas/core/indexing.py in _convert_to_indexer(self, obj, axis, is_setter, raise_missing)
   1352                 kwargs = {'raise_missing': True if is_setter else
   1353                           raise_missing}
-> 1354                 return self._get_listlike_indexer(obj, axis, **kwargs)[1]
   1355         else:
   1356             try:

~/venv/lib/python3.6/site-packages/pandas/core/indexing.py in _get_listlike_indexer(self, key, axis, raise_missing)
   1159         self._validate_read_indexer(keyarr, indexer,
   1160                                     o._get_axis_number(axis),
-> 1161                                     raise_missing=raise_missing)
   1162         return keyarr, indexer
   1163 

~/venv/lib/python3.6/site-packages/pandas/core/indexing.py in _validate_read_indexer(self, key, indexer, axis, raise_missing)
   1250             if not(self.name == 'loc' and not raise_missing):
   1251                 not_found = list(set(key) - set(ax))
-> 1252                 raise KeyError("{} not in index".format(not_found))
   1253 
   1254             # we skip the warning on Categorical/Interval

KeyError: "[Timestamp('2016-06-16 00:00:00')] not in index"

Answer 1

您可以使用Index.isin进行测试成员资格，然后将列强制转换为整数，以实现1/0到Series的映射，也不必转换为dates_list = ['2016-06-16','2016-06-23', '2016-06-24', '2016-07-02', '2016-07-13'] key_dates = pd.to_datetime(dates_list) tweet_trend['Important Events'] = df.index.isin(key_dates) tweet_trend['values'] = tweet_trend['Important Events'].astype(int)：

url

每天可视化覆盖有关键事件的数据计数

1 个答案: