使用 Pandas 将字符串与 JSON 进行比较

Question

我正在使用 Pandas 的 DataFrame。我有这样的情况下，合并2个文件后： fr.item = "ipod"; fr.bucket = {'ipad':34,'ipod':36,'iwatch':27} 注：数据类型在Series这里有没有办法可以在这里检查存储桶 ( ipod) 中的项目并获取值 ( 36)？此外，在没有循环的情况下执行此操作是值得赞赏的，因为我正在做一列到列的比较。输入item    bucketipod    {'ipad':34,'ipod':36,'iwatch':27}ipad    {'ipad':87,'ipod':31,'iwatch':62}输出3687

Answer 1

同意@bazingaa，只需使用：

fr.bucket[fr.item]

因此，获取带有命名的字典键，ipod然后像上面一样获取它的值，就是这样。

Answer 2

item=['ipod','ipad']

bucket=[{'ipad':34,'ipod':36,'iwatch':27},{'ipad':87,'ipod':31,'iwatch':62}]

result_output=[]    # Defining for output

counter=0           # For initialising the counter through the bucket's elements

for key in item:    # For each row value in column1. Column1 is item.

   temp_bucket=dict(bucket[counter]) # For each column's value,it is as a dictionary

   if key in temp_bucket:   # Checking if the column1's value is present in the dictionary of that row (column2)   

      length_1=len(bucket)-1                 # Need to subtract 1 as python is based on 0 indexing     

      result_output.append(temp_bucket[key]) # Appending each row output to the result list.

      if counter<length_1:                   # Need to check if there is sufficient element is present in column2. Otherwise throw error for index.

         counter=counter+1                  # for checking the next element of column2

print(result_output) # 输出列表

Answer 3

我试过了，它奏效了

对于 df.index 中的 i：

#For Bucket

val_bucket=ast.literal_eval(bucket[i])

for key, val in val_bucket.items():

    if my_items[i]== key:

        print ("Value",val)

         break

因此，我已将那些 JSON 值（串联）转换为 dict 并提取值