Reputation: 27
I am using a Yahoo finance Python library to grab accounting financial data to do some basic analysis. All of the financial statement data comes in JSON format. I want the data to be in a tabular format as I typically see in a Python dataframe. Hello there are several wrappers around the data and I'm not sure how to remove those so that I can get my data into a simple columns and rows dataframe. Here is what the Python looks like:
{
"incomeStatementHistory":{
"F":[
{
"2019-12-31":{
"researchDevelopment":"None",
"effectOfAccountingCharges":"None",
"incomeBeforeTax":-640000000,
"minorityInterest":45000000,
"netIncome":47000000,
"sellingGeneralAdministrative":10218000000,
"grossProfit":12876000000,
"ebit":2658000000,
"operatingIncome":2658000000,
"otherOperatingExpenses":"None",
"interestExpense":-1049000000,
"extraordinaryItems":"None",
Upvotes: 0
Views: 129
Reputation: 5648
you don't have the full response so it's difficult to tell if this will be what you want
d = {
"incomeStatementHistory":{
"F":[
{
"2019-12-31":{
"researchDevelopment":"None",
"effectOfAccountingCharges":"None",
"incomeBeforeTax":-640000000,
"minorityInterest":45000000,
"netIncome":47000000,
"sellingGeneralAdministrative":10218000000,
"grossProfit":12876000000,
"ebit":2658000000,
"operatingIncome":2658000000,
"otherOperatingExpenses":"None",
"interestExpense":-1049000000,
"extraordinaryItems":"None",}}]}}
pd.json_normalize(d['incomeStatementHistory']['F'])
Output:
2019-12-31.researchDevelopment 2019-12-31.effectOfAccountingCharges 2019-12-31.incomeBeforeTax ... 2019-12-31.otherOperatingExpenses 2019-12-31.interestExpense 2019-12-31.extraordinaryItems
0 None None -640000000 ... None -1049000000 None
[1 rows x 12 columns]
Upvotes: 1
Reputation: 67
You should use Pandas Here its a tutorial of how to do that with pandas
Also you could check this question
Upvotes: 1