python - 从 pickle 读取时，数据帧被解析为元组

Question

我有一个 pickle 文件，其中包含数据帧的字典。作为数据清理脚本的一部分，我加载此 pickle 并对某些(但不是全部)数据帧进行额外处理，然后覆盖要稍后由模拟程序拾取和加载的 pickle。

当我在处理后读取pickle时，除了两个值之外的所有值都被正确解包并解析为数据帧，但这两个值被读取为元组。由于这两个实际上不需要在此特定数据清理脚本中进行任何更改，因此除以下内容外，脚本不会处理它们:

#start of script, read in the pickle assign the dfs for later use.
input_file = sys.argv[1]
with open(input_file, 'rb') as handle:
  data = pickle.load(handle)


trips      = data['trips']       # this sees additional processing, is correctly written out as a DF. 
stops      = data['stops']       # this sees additional processing, is correctly written out as a DF.
stop_times = data['stop_times'], # NO additional processing, is INCORRECTLY written out as a tuple.
road_segs  = data['road_segs'],  # NO additional processing, is INCORRECTLY written out as a tuple.
seg_props  = data['seg_props']   # NO additional processing, is correctly written out as a df.


... # do additional processing on trips and stops


#Output the update DFs and carry the unaltered DFs through to overwrite the original pickle.

data = {
  "trips":      trips,
  "stops":      stops,
  "stop_times": stop_times,
  "road_segs":  road_segs,
  "seg_props":  seg_props
}

with open(input_file, 'wb') as handle:
  pickle.dump(data, handle, protocol=4)

如果我在运行此脚本之前阅读pickle，我会得到以下内容。

[type(val) for val in gtfs.values()]                                                                                                                                                    
#output
[pandas.core.frame.DataFrame,
 geopandas.geodataframe.GeoDataFrame,
 pandas.core.frame.DataFrame,
 pandas.core.frame.DataFrame,
 pandas.core.frame.DataFrame]

及之后:

[type(val) for val in gtfs.values()]                                                                                                                                                    
Out[17]: 
[pandas.core.frame.DataFrame,
 pandas.core.frame.DataFrame,
 tuple,
 tuple,
 pandas.core.frame.DataFrame]

这些元组也高度嵌套:

(((                                   trip_id stop_id  stop_duation
   0        15243854-AUG19-MVS-BUS-Weekday-01   17894           0.0
   1        15243854-AUG19-MVS-BUS-Weekday-01   17897           0.0
   2        15243854-AUG19-MVS-BUS-Weekday-01   17900           0.0

   [2812369 rows x 3 columns],),),)

Answer 1

我有两个悬挂逗号

stop_times = data['stop_times'],
road_segs  = data['road_segs'],

在我的导入中，这是造成这种情况的原因。我无法理解，在一遍又一遍地盯着它看之后，我怎么没有注意到这一点。