Question

我有一个python dict / hashmap：

Generated Code      |      Contract Date      |     Contract Time
    null            |         201607          |          1:31:01

我正在尝试使用相应的地图值替换DataFrame对象中的值。我用下面的预期输出写了一个例子。

我有3列数据。如果生成的代码为null，我将使用Contract Time + map value填充该列。

Generated Code      |      Contract Date      |     Contract Time
    1:31:016        |         201607          |          1:31:01

预期产出：

yearCode = df['Contract Date'].astype(str).apply(lambda x: x[:4])

df.loc[df["Generated Code"].isnull(),'Generated Code'] = df['Contract Time'] + yearMapping.get(yearCode)

到目前为止我在做什么：

$type = 'testing';

$stmt = $con->prepare("INSERT INTO   contents (type, reporter, description) VALUES (?, ?, ?)");
         $stmt->bind_param("sss", $type , 'john', 'whatever');
         $stmt->execute();
    $stmt->close();

我一直收到错误消息： TypeError：＆＃39; Series＆＃39;对象是可变的，因此它们不能被散列

这甚至可以吗？

Answer 1

我认为您需要null从NaN到Series，然后replace以及最后yearCode dict indexing with str { {1}}：

df['Generated Code'] = df['Generated Code'].replace({'null':np.nan})

yearMapping = {"2016":"6", "2017":"7", "2018":"8", "2019":"9"}

yearCode = df['Contract Date'].astype(str).str[:4]

df.loc[df["Generated Code"].isnull(),'Generated Code'] = 
df['Contract Time'] + yearCode.map(yearMapping)
print (df)
  Generated Code  Contract Date Contract Time
0       1:31:016         201607       1:31:01

另一种解决方案是改变条件：

yearMapping = {"2016":"6", "2017":"7", "2018":"8", "2019":"9"}
yearCode = df['Contract Date'].astype(str).str[:4]
df.loc[df["Generated Code"] == 'null','Generated Code'] = 
df['Contract Time'] + yearCode.map(yearMapping)
print (df)
  Generated Code  Contract Date Contract Time
0       1:31:016         201607       1:31:01

导致对象的字典查找是可变的，因此它们不能被散列错误

1 个答案: