从 csv 加载 pandas 数据框时，将数据框单元格内的列表分解为行的代码失败。

Question

我一直在尝试将数据框中的列表分解为扩展/分解的列，如堆栈溢出 How to explode a list inside a Dataframe cell into separate rows 中所述

我遇到了麻烦。

我从示例中获得了 stackoverflow 代码。但我无法让它适用于我的个人数据文件（在我使用的 csv 文件中`pd.read_csv。

然后我简化了代码以删除一个不必要的列。我得到了简化的示例代码。然后我尝试再次加载我的 .csv。再一次，它失败了。

因此，我通过将简化示例中的数据框写入新的 csv 文件，使用 pd.read_csv` 加载该文件，然后重新运行简化的“explode”代码，从而将我的文件排除在外。我得到了同样的错误。代码和错误输出如下。

import pandas as pd

#Create The DataFrame 

df = (pd.DataFrame({ 
                'opponent': ['76ers', 'blazers', 'bobcats'], 
                'nearest_neighbors': [['Zach LaVine', 'Jeremy Lin',       'Nate Robinson', 'Isaia']] * 3})
  .set_index([ 'opponent']))

#Explode The Data Frame

(pd.melt(df.nearest_neighbors.apply(pd.Series).reset_index(), 
     id_vars=[ 'opponent'],
     value_name='nearest_neighbors')
 .set_index([ 'opponent'])
 .drop('variable', axis=1)
 .dropna()
 .sort_index()
)

#Save DF to CSV

df.to_csv("Baskets.CSV")
#Load DF to CSV
df = pd.read_csv("Baskets.csv")

# Re Run Explode Code on csv 

(pd.melt(df.nearest_neighbors.apply(pd.Series).reset_index(), 
         id_vars=[ 'opponent'],
         value_name='nearest_neighbors')
 .set_index([ 'opponent'])
 .drop('variable', axis=1)
 .dropna()
 .sort_index()
 )






KeyError                                  Traceback (most recent call last)
~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2441             try:
-> 2442                 return self._engine.get_loc(key)
   2443             except KeyError:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'opponent'

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
<ipython-input-25-6ffdc50e8f2c> in <module>()
      1 (pd.melt(df.nearest_neighbors.apply(pd.Series).reset_index(), 
      2              id_vars=[ 'opponent'],
----> 3              value_name='nearest_neighbors')
      4      .set_index([ 'opponent'])
      5      .drop('variable', axis=1)

~/anaconda3/lib/python3.6/site-packages/pandas/core/reshape/reshape.py in melt(frame, id_vars, value_vars, var_name, value_name, col_level)
    761     mdata = {}
    762     for col in id_vars:
--> 763         mdata[col] = np.tile(frame.pop(col).values, K)
    764 
    765     mcolumns = id_vars + var_name + [value_name]

~/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py in pop(self, item)
    548         Return item and drop from frame. Raise KeyError if not found.
    549         """
--> 550         result = self[item]
    551         del self[item]
    552         try:

~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py in __getitem__(self, key)
   1962             return self._getitem_multilevel(key)
   1963         else:
-> 1964             return self._getitem_column(key)
   1965 
   1966     def _getitem_column(self, key):

~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py in _getitem_column(self, key)
   1969         # get column
   1970         if self.columns.is_unique:
-> 1971             return self._get_item_cache(key)
   1972 
   1973         # duplicate columns & possible reduce dimensionality

~/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py in _get_item_cache(self, item)
   1643         res = cache.get(item)
   1644         if res is None:
-> 1645             values = self._data.get(item)
   1646             res = self._box_item_values(item, values)
   1647             cache[item] = res

~/anaconda3/lib/python3.6/site-packages/pandas/core/internals.py in get(self, item, fastpath)
   3588 
   3589             if not isnull(item):
-> 3590                 loc = self.items.get_loc(item)
   3591             else:
   3592                 indexer = np.arange(len(self.items))[isnull(self.items)]

~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2442                 return self._engine.get_loc(key)
   2443             except KeyError:
-> 2444                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   2445 
   2446         indexer = self.get_indexer([key], method=method, tolerance=tolerance)

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'opponent'

Answer 1

当您保存到 csv 文件并从中读取时，您的初始索引将被重置为默认索引。要修复它，您需要读取将 index_col 设置为 opponent 的 csv。

代替：

#Load DF to CSV
df = pd.read_csv("Baskets.csv")

尝试使用：

#Load DF to CSV
df = pd.read_csv("Baskets.csv", index_col='opponent')

要将nearest_neighbors 列转换为列表，您还需要这样做：

from ast import literal_eval

df.nearest_neighbors=df.nearest_neighbors.apply(literal_eval)

在那之后，我就可以开始熔化了：

(pd.melt(df.nearest_neighbors.apply(pd.Series).reset_index(), 
     id_vars=[ 'opponent'],
     value_name='nearest_neighbors')
 .set_index([ 'opponent'])
 .drop('variable', axis=1)
 .dropna()
 .sort_index()
)

输出：

             nearest_neighbors
opponent                  
76ers          Zach LaVine
76ers           Jeremy Lin
76ers        Nate Robinson
76ers                Isaia
blazers        Zach LaVine
blazers         Jeremy Lin
blazers      Nate Robinson
blazers              Isaia
bobcats        Zach LaVine
bobcats         Jeremy Lin
bobcats      Nate Robinson
bobcats              Isaia