Question

我有一个数据框被附加到一个循环中（如果有一个更好的方法来将行添加到数据框的末尾然后建议欢迎）。以下代码片段给出了错误：

import pandas as pd
import pytz
import datetime

x = 'astring'
t = (datetime.datetime(2018, 5, 31, 13, 15, 17, tzinfo=pytz.utc), datetime.datetime(2100, 5, 31, tzinfo=pytz.utc))
df = pd.DataFrame(columns=['a', 'b', 'c'])
df = df.append({'a': x, 'b': t[0], 'c': t[1]}, ignore_index=True)

TypeError                                 Traceback (most recent call last)
<ipython-input-161-0df455a78607> in <module>()
      2 t = (datetime.datetime(2018, 5, 31, 13, 15, 17, tzinfo=pytz.utc), datetime.datetime(2100, 5, 31, tzinfo=pytz.utc))
      3 df = pd.DataFrame(columns=['a', 'b', 'c'])
----> 4 df = df.append({'a': x, 'b': t[0], 'c': t[1]}, ignore_index=True)

/usr/local/envs/py3env/lib/python3.5/site-packages/pandas/core/frame.py in append(self, other, ignore_index, verify_integrity)
   5192 
   5193     _shared_docs['pivot_table'] = """
-> 5194         Create a spreadsheet-style pivot table as a DataFrame. The levels in
   5195         the pivot table will be stored in MultiIndex objects (hierarchical
   5196         indexes) on the index and columns of the result DataFrame

/usr/local/envs/py3env/lib/python3.5/site-packages/pandas/core/reshape/concat.py in concat(objs, axis, join, join_axes, ignore_index, keys, levels, names, verify_integrity, copy)
    211     a  1
    212     >>> df6 = pd.DataFrame([2], index=['a'])
--> 213     >>> df6
    214        0
    215     a  2

/usr/local/envs/py3env/lib/python3.5/site-packages/pandas/core/reshape/concat.py in get_result(self)
    406             mgrs_indexers = []
    407             for obj in self.objs:
--> 408                 mgr = obj._data
    409                 indexers = {}
    410                 for ax, new_labels in enumerate(self.new_axes):

/usr/local/envs/py3env/lib/python3.5/site-packages/pandas/core/internals.py in concatenate_block_managers(mgrs_indexers, axes, concat_axis, copy)
   5201     expanded label indexer
   5202     """
-> 5203     mult = np.array(shape)[::-1].cumprod()[::-1]
   5204     return _ensure_platform_int(
   5205         np.sum(np.array(labels).T * np.append(mult, [1]), axis=1).T)

/usr/local/envs/py3env/lib/python3.5/site-packages/pandas/core/internals.py in concatenate_join_units(join_units, concat_axis, copy)
   5330 
   5331     # see if we are only masking values that if putted
-> 5332     # will work in the current dtype
   5333     try:
   5334         nn = n[m]

/usr/local/envs/py3env/lib/python3.5/site-packages/pandas/core/internals.py in <listcomp>(.0)
   5330 
   5331     # see if we are only masking values that if putted
-> 5332     # will work in the current dtype
   5333     try:
   5334         nn = n[m]

/usr/local/envs/py3env/lib/python3.5/site-packages/pandas/core/internals.py in get_reindexed_values(self, empty_dtype, upcasted_na)
   5601     for ax, indexer in indexers.items():
   5602         mgr_shape[ax] = len(indexer)
-> 5603     mgr_shape = tuple(mgr_shape)
   5604 
   5605     if 0 in indexers:

TypeError: data type not understood

但是，以下代码段工作正常：

x = 'astring'
t = (datetime.datetime(2018, 5, 31, 13, 15, 17), datetime.datetime(2100, 5, 31))
df = pd.DataFrame(columns=['a', 'b', 'c'])
df = df.append({'a': x, 'b': t[0], 'c': t[1]}, ignore_index=True)

陌生人，这也没关系：

t = (datetime.datetime(2018, 5, 31, 13, 15, 17, tzinfo=pytz.utc), datetime.datetime(2100, 5, 31, tzinfo=pytz.utc))
df = pd.DataFrame(columns=['b', 'c'])
df = df.append({'b': t[0], 'c': t[1]}, ignore_index=True)

我错过了什么？我只是在这里添加更多细节因为StackOverflow抱怨我“需要更多细节”来提交这个问题，因为我觉得特别冗长是一件好事。谁知道？

pandas==0.23.0
pytz==2016.7

Answer 1

这似乎是pandas和pytz库版本之间的兼容性问题。

我能够重现您在Datalab中获得的错误，并且我能够通过升级到pandas==0.23.0来解决它（我使用了全新Datalab实例附带的默认0.22.0 ）和pytz==2018.4。另外，根据我见过的其他一些Stack Overflow帖子，numpy可能存在一些问题，因此只是进行复核，我使用的是numpy==1.14.3。

要升级库版本，您应该：

创建一个新笔记本，并在第一个单元格中运行命令!pip install --upgrade pandas。这为我安装了pytz==2018.4，但如果不是这样，您也可以尝试手动安装。
通过单击Datalab中的“重置会话”选项重新启动内核。
再次运行您的代码，看看它现在是否有效：

添加以下行以检查我提到的版本是否正在使用中：

print(pd.__version__)
print(pytz.__version__)
print(np.__version__)

为什么pandas DataFrame.append（）会给出时区值错误？

1 个答案: