Question

我的文件包含公司，记录ID，销售等列。当我在将文件加载到pandas数据框后首次尝试查找其数据类型时，它列出了float / int几列。所以我将它们更改为字符串，如下所示：

data = pd.read_csv(filepath)
    print(data.dtypes)

Company Code          object
SiteCode               int64
Product Name          object
RECORD ID             int64
Tank ID                int64
Date                   int64
Sale Volume          float64
Deliveries Volume      int64
Dip Volume           float64

然后在将输出写入文件之前，将它们的类型更改为字符串；

>   data['RECORD ID'] = data['RECORD ID'].astype(str)
>      data['Tank ID'] = data['Tank ID'].astype(str)

我到了；

    return self._engine.get_loc(key)
  File "pandas/_libs/index.pyx", line 107, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/index.pyx", line 131, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/hashtable_class_helper.pxi", line 1607, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas/_libs/hashtable_class_helper.pxi", line 1614, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'RECORD ID'

如果我评论recordid并让Tankid进行转换，那么我得到TankId的相同键错误，为什么？

这是示例csv； SIRA RECORD ID和TANK ID列给出了问题

 Company Code,SiteCode,Product Name,SIRA RECORD ID,Tank ID,Date,Sale Volume,Deliveries Volume,Dip Volume
    XXX,20995,27PMAXDSL,3535352,4,20191004,4383.49,12902,16000
    XXX,20995,02ULP,3535351,3,20191004,8221.573,15996,9987.32
    XXX,20995,02ULP,3535350,2,20191004,7303.1,8201,11200

Answer 1

如果需要将所有列更好地字符串化，请在dtype中使用参数read_csv：

data = pd.read_csv(filepath, dtype=str)

Answer 2

尝试以下代码。索引列表直接传递给熊猫，而不直接传递给熊猫

SET,FW.O,AS,num:+18700000,num:+12355,#(5th field matched with FWmatch num:+123)
SET,IT,AS,num:+22211111,num:+12355,#(4th field matched with ITmatch num:+222)
SET,FW.O,AS,num:+177232,num:+12355,#(5th field matched with FWmatch num:+123)

Answer 3

代替手动输入列名，请尝试以下方法作为测试：

for col in data.columns:
    data[col] = data[col].astype(str)

这也应该适用于整个数据框

data = data.astype('str')

为什么即使列存在于熊猫中也为什么会出现Key错误？

3 个答案: