i´ve json list and I can´t convert to Pandas dataframe (varios rows and 19 columns)
Link to response : https://www.byma.com.ar/wp-admin/admin-ajax.php?action=get_historico_simbolo&simbolo=INAG&fecha=01-02-2018
json response:
[{"Apertura":35,"Apertura_Homogeneo":35,"Cantidad_Operaciones":1,"Cierre":35,"Cierre_Homogeneo":35,"Denominacion":"INSUMOS AGROQUIMICOS S.A.","Fecha":"02\/02\/2018","Maximo":35,"Maximo_Homogeneo":35,"Minimo":35,"Minimo_Homogeneo":35,"Monto_Operado_Pesos":175,"Promedio":35,"Promedio_Homogeneo":35,"Simbolo":"INAG","Variacion":-5.15,"Variacion_Homogeneo":0,"Vencimiento":"48hs","Volumen_Nominal":5},
{"Apertura":34.95,"Apertura_Homogeneo":34.95,"Cantidad_Operaciones":2,"Cierre":34.95,"Cierre_Homogeneo":34.95,"Denominacion":"INSUMOS AGROQUIMICOS S.A.","Fecha":"05\/02\/2018","Maximo":34.95,"Maximo_Homogeneo":34.95,"Minimo":34.95,"Minimo_Homogeneo":34.95,"Monto_Operado_Pesos":5243,"Promedio":-79228162514264337593543950335,"Promedio_Homogeneo":-79228162514264337593543950335,"Simbolo":"INAG","Variacion":-0.14,"Variacion_Homogeneo":-0.14,"Vencimiento":"48hs","Volumen_Nominal":150},
{"Apertura":32.10,"Apertura_Homogeneo":32.10,"Cantidad_Operaciones":2,"Cierre":32.10,"Cierre_Homogeneo":32.10,"Denominacion":"INSUMOS AGROQUIMICOS S.A.","Fecha":"07\/02\/2018","Maximo":32.10,"Maximo_Homogeneo":32.10,"Minimo":32.10,"Minimo_Homogeneo":32.10,"Monto_Operado_Pesos":98756,"Promedio":32.10,"Promedio_Homogeneo":32.10,"Simbolo":"INAG","Variacion":-8.16,"Variacion_Homogeneo":-8.88,"Vencimiento":"48hs","Volumen_Nominal":3076}]
I use the next piece of code to convert this json to dataframe:
def getFinanceHistoricalStockFromByma(tickerList):
dataFrameHistorical = pd.DataFrame()
for item in tickerList:
url = 'https://www.byma.com.ar/wp-admin/admin-ajax.php?action=get_historico_simbolo&simbolo=' + item + '&fecha=01-02-2018'
response = requests.get(url)
if response.content : print 'ok info Historical Stock'
data = response.json()
dfItem = jsonToDataFrame(data)
dataFrameHistorical = dataFrameHistorical.append(dfItem, ignore_index=True)
return dataFrameHistorical
def jsonToDataFrame(jsonStr):
return json_normalize(jsonStr)
The result of json_normalize is 1 row and a lot of columns. How can I convert this json response to 1 row per list?
Thanks!
You can convert JSON to Pandas DataFrame by simply using read_json() . Just pass JSON string to the function. It takes multiple parameters, for our case I am using orient that specifies the format of JSON string. This function is also used to read JSON files into pandas DataFrame.
Reading JSON Files using Pandas To read the files, we use read_json() function and through it, we pass the path to the JSON file we want to read. Once we do that, it returns a “DataFrame”( A table of rows and columns) that stores data.
If you change this line in your function: dfItem = jsonToDataFrame(data)
to:
dfItem = pd.DataFrame.from_records(data)
it should work. I tested your function with this line replaced, using ['INAG'] as a parameter passed to your getFinanceHistoricalStockFromByma
function, and it returned a DataFrame.
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