如何将以下 JSON 操作到所需的 Pandas Dataframe 中？

Question

Here is the JSON I am working with:

 { "2021-05-24": { "RSI": "75.1354" }, "2021-05-21": { "RSI": "74.5561" }, "2021-05-14": { "RSI": "78.1510" }, "2021-05-07": { "RSI": "75.3214" }, "2021-04-30": { "RSI": "74.1698" } }

I need to transform this JSON into the Following Pandas Dataframe:

         Date         RSI
0        2021-05-24   75.1354
1        2021-05-21   74.5561
2        2021-05-14   78.1510
...

The dataframe that pandas is defaulting to:

       2021-05-24       2021-05-21      2021-05-14 
RSI    37.8626          39.4409         40.3654    

Basically I want to filter the dataframe to exclude RSI Values that are >25 and < 75. If I have the desired dataframe, I can simply filter by the 'RSI' Index. However, I cannot figure out how to filter the current dataframe. Any help is appreciated, and I am pretty new to Pandas.

Answer 1

Try with

out = df.T.reset_index()

Answer 2

data={
    "2021-05-24": {
        "RSI": "75.1354"
    },
    "2021-05-21": {
        "RSI": "74.5561"
    },
    "2021-05-14": {
        "RSI": "78.1510"
    },
    "2021-05-07": {
        "RSI": "75.3214"
    },
    "2021-04-30": {
        "RSI": "74.1698"
    }
}

You can use DataFrame.from_dict() method:

df=pd.DataFrame.from_dict(data,orient='index')

OR

Use Transpose attribute:

df=pd.Dataframe(data).T

OR

Use transpose() method:

df=pd.DataFrame(data).transpose()

Answer 3

You can use pandas.DataFrame.melt()

df = pd.read_json('<your_file>.json')
df.melt(var_name='Date', value_name='RSI')

        Date      RSI
0 2021-05-24  75.1354
1 2021-05-21  74.5561
2 2021-05-14  78.1510
3 2021-05-07  75.3214
4 2021-04-30  74.1698

Or, because your json orientation is index , you can set the orient parameter of pd.read_json() to "index"

pd.read_json('<your_file>.json', orient='index')

                RSI
2021-04-30  74.1698
2021-05-07  75.3214
2021-05-14  78.1510
2021-05-21  74.5561
2021-05-24  75.1354