[英]Replacing None with a list within a dataframe
I have the below dataframe which comes from a JSON我有以下来自 JSON 的数据框
0 [0, 5.9, 4] [1, 6, 23] [2, 6.2, 2]
1 [0, 48, 3.11] [1, 50, 10] [2, 55, 13.1]
2 [0, 1.42, 90.26] [1, 1.43, 91.8] [2, 1.44, 121]
3 [0, 970, 18.41] [1, 990, 1.53] None
4 [0, 970, 18.42] [1, 990, 1.55] [2, 1000, 22.5]
5 [0, 740, 9.37] [1, 990, 1.53] None
6 [0, 740, 9.37] [1, 900, 2.21] [2, 990, 1.55]
7 [0, 970, 18.45] [1, 990, 1.6] None
8 [0, 740, 9.39] [1, 990, 2.55] None
9 [0, 970, 18.4] [1, 990, 1.6] None
10 [0, 42, 1.1] [1, 85, 1.91] [2, 90, 1.04]
trying to format ready for db insertion, i am splitting using .tolist() but getting error for None entries.试图格式化为数据库插入做好准备,我正在使用 .tolist() 进行拆分,但出现 None 条目错误。
tried fillna and replace to insert a dummy list ie [0,0,0] but will only let me replace with a string.尝试使用 fillna 和 replace 插入一个虚拟列表,即 [0,0,0] 但只会让我用字符串替换。 Any suggestions welcome.欢迎任何建议。
this works这行得通
#df_split_batl = df_split_batl.fillna('xx') #df_split_batl = df_split_batl.replace('xx','yy') #df_split_batl = df_split_batl.fillna('xx') #df_split_batl = df_split_batl.replace('xx','yy')
but these dont但这些不
#df_split_batl = df_split_batl.fillna([0,0,0]) #df_split_batl = df_split_batl.fillna([0,0,0])
#df_split_batl = df_split_batl.fillna('xx') #df_split_batl = df_split_batl.fillna('xx')
#df_split_batl = df_split_batl.replace('xx',[0,0,0]) #df_split_batl = df_split_batl.replace('xx',[0,0,0])
Check the following link, it might be helpful for your case: Replace NaN with empty list in a pandas dataframe检查以下链接,它可能对您的情况有帮助: Replace NaN with empty list in a pandas dataframe
Instead of replacing it with an empty list, you'll replace it with a list containing elements.不是用空列表替换它,而是用包含元素的列表替换它。
RGS20 :) RGS20 :)
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