python之保存和导出 python pandas 数据框的数据类型信息

我有一个名为 df 的 pandas DataFrame。使用 df.dtypes 我可以在屏幕上打印:

arrival_time      object 
departure_time    object 
drop_off_type      int64 
extra             object 
pickup_type        int64 
stop_headsign     object 
stop_id           object 
stop_sequence      int64 
trip_id           object 
dtype: object 

我想保存这些信息，以便我可以将它与其他数据进行比较，在别处进行类型转换等。我想将它保存到本地文件，在数据不能去的另一个程序中的其他地方恢复它。但我无法弄清楚如何。显示各种转换的结果。

df.dtypes.to_dict() 
{'arrival_time': dtype('O'), 
 'departure_time': dtype('O'), 
 'drop_off_type': dtype('int64'), 
 'extra': dtype('O'), 
 'pickup_type': dtype('int64'), 
 'stop_headsign': dtype('O'), 
 'stop_id': dtype('O'), 
 'stop_sequence': dtype('int64'), 
 'trip_id': dtype('O')} 
---- 
df.dtypes.to_json() 
'{"arrival_time":{"alignment":4,"byteorder":"|","descr":[["","|O"]],"flags":63,"isalignedstruct":false,"isnative":true,"kind":"O","name":"object","ndim":0,"num":17,"str":"|O"},"departure_time":{"alignment":4,"byteorder":"|","descr":[["","|O"]],"flags":63,"isalignedstruct":false,"isnative":true,"kind":"O","name":"object","ndim":0,"num":17,"str":"|O"},"drop_off_type":{"alignment":4,"byteorder":"=","descr":[["","<i8"]],"flags":0,"isalignedstruct":false,"isnative":true,"kind":"i","name":"int64","ndim":0,"num":9,"str":"<i8"},"extra":{"alignment":4,"byteorder":"|","descr":[["","|O"]],"flags":63,"isalignedstruct":false,"isnative":true,"kind":"O","name":"object","ndim":0,"num":17,"str":"|O"},"pickup_type":{"alignment":4,"byteorder":"=","descr":[["","<i8"]],"flags":0,"isalignedstruct":false,"isnative":true,"kind":"i","name":"int64","ndim":0,"num":9,"str":"<i8"},"stop_headsign":{"alignment":4,"byteorder":"|","descr":[["","|O"]],"flags":63,"isalignedstruct":false,"isnative":true,"kind":"O","name":"object","ndim":0,"num":17,"str":"|O"},"stop_id":{"alignment":4,"byteorder":"|","descr":[["","|O"]],"flags":63,"isalignedstruct":false,"isnative":true,"kind":"O","name":"object","ndim":0,"num":17,"str":"|O"},"stop_sequence":{"alignment":4,"byteorder":"=","descr":[["","<i8"]],"flags":0,"isalignedstruct":false,"isnative":true,"kind":"i","name":"int64","ndim":0,"num":9,"str":"<i8"},"trip_id":{"alignment":4,"byteorder":"|","descr":[["","|O"]],"flags":63,"isalignedstruct":false,"isnative":true,"kind":"O","name":"object","ndim":0,"num":17,"str":"|O"}}' 
---- 
json.dumps( df.dtypes.to_dict() ) 
... 
TypeError: dtype('O') is not JSON serializable 
 
---- 
list(xdf.dtypes) 
[dtype('O'), 
 dtype('O'), 
 dtype('int64'), 
 dtype('O'), 
 dtype('int64'), 
 dtype('O'), 
 dtype('O'), 
 dtype('int64'), 
 dtype('O')] 

如何保存和导出/归档 pandas DataFrame 的 dtype 信息？

请您参考如下方法:

pd.DataFrame.dtypes返回 pd.Series目的。这意味着您可以像操作 Pandas 中的任何常规系列一样操作它:

df = pd.DataFrame({'A': [''], 'B': [1.0], 'C': [1], 'D': [True]}) 
 
res = df.dtypes.to_frame('dtypes').reset_index() 
 
print(res) 
 
  index   dtypes 
0     A   object 
1     B  float64 
2     C    int64 
3     D     bool 

输出到 csv/excel/pickle

然后您可以使用您通常使用的任何方法来存储数据帧，例如 to_csv , to_excel , to_pickle等。不推荐分发 pickle，因为它依赖于版本。

输出为json

如果您希望以字典的形式轻松存储和加载，流行的格式是json。如您所见，您需要先转换为 str 类型:

import json 
 
# first create dictionary 
d = res.set_index('index')['dtypes'].astype(str).to_dict() 
 
with open('types.json', 'w') as f: 
    json.dump(d, f) 
 
with open('types.json', 'r') as f: 
    data_types = json.load(f) 
 
print(data_types) 
 
{'A': 'object', 'B': 'float64', 'C': 'int64', 'D': 'bool'}