I am still a newbie with Python and working on my first REST API. I have a JSON file that has a few levels. When I create the data frame with pandas, no matter what I try I cannot access…
I have a folder structure that looks like this: 1. data 1.1. ABC 1.1.1 monday_data monday.json 1.1.2 tuesday_data tuesday.json 1.2. YXZ 1.2.1 wednesday_data wednesday.json 1.2.2 etc I want to unpack all of these json files into a pandas dataframe in…
I have a json string column in a dataframe that looks like this. {"columns":["ApplicationNum","eads59Us01S","HouseDeal_flag","Liability_Asset_Ratio","CBRAvailPcnt","CMSFairIsaacScore","OweTaxes_or_IRAWithdrawalHistry","eads14Fi02S","GuarantorCount","CBRRevMon","CBRInstalMon","CMSApprovedToRequested","SecIncSource","eads59Us01S_4","Liability_Asset_Ratio_40_90","CBRAvailPcnt_20_95","CMSFairIsaacScore_Fund","eads14Fi02S_2","InstalMonthlyPayments_400_3k","RevolvingMonthlyPayments_1k_cap","ApprovedToRequested_0_100","NoSecIncome","coef_eads59Us01S_4","coef_HouseDeal_flag","coef_Liability_Asset_Ratio_40_90","coef_CBRAvailPcnt_20_95","coef_CMSFairIsaacScore_Fund","coef_OweTaxes_or_IRAWithdrawalHistry","coef_eads14Fi02S_2","coef_GuarantorCount","coef_RevolvingMonthlyPayments_1k_cap","coef_InstalMonthlyPayments_400_3k","coef_ApprovedToRequested_0_100","coef_NoSecIncome","coef_Intercept"],"data":[[569325.0,2,0.0,1,92,825,0.0,4,1.0,74,854,0.51,2,2.0,0.9,92.0,825.0,4.0,854.0,1000.0,0.51,0.0,0.11716245,0.299528064,0.392119645,-0.010826643,-0.004957868,0.339407077,0.061509795,0.3685047,0.000167603,0.000225742,0.902205454,-0.371734864,2.788087559]]} I have a columns tag in there with a list of column values, and a data tag in there with the corresponding list of values for…
I am new here , need some help with writing to json file: I have a dataframe with below values, which is created by reading a excel file need to write this to json file with object as column dtls…
So I'm building an eBay webscraper for work (I should note that I am incredibly new to programming in general, and am entirely self-taught using the internet), and I have made it functionin. I am building this with Python 3.11,…
I want to loop through my data and save every component based data in separate sheet in the same excel workbook in S3 bucket. Dataframe df looks as below: Below is my code: today = datetime.datetime.now().strftime('%m_%d_%Y_%H_%M_%S') components=["COMP1","COMP2","COMP3"] filename = 'auto_export_'+today…
Here is my pd.DataFrame with its metadata column: date metadata 0 2022-12-03 [{'key': 'key1', 'value': value0.1'}, {'key': 'key2', 'value': value0.2'}, {'key': 'key3', 'value': value0.3'}] 1 2022-12-07 [{'key': 'key1', 'value': value1.1'}, {'key': 'key2', 'value': value1.2'}, {'key': 'key3', 'value': value1.3'}] 2 2022-12-02…
Am a new user on ubuntu version 20.04. The fresh install comes with python 3.8, so i upgrade to latest 3.11. I do the usual pip install pandas. Note i also try pip3 install pandas for good measure. create a…
I'm trying with python to convert a nested json content into a dataframe : { "end_date":"2023-02-02-00:00", "price":{ "2023-01-30":{ "CHFEUR":{ "close":0.99612, "high":0.99939, "low":0.99408, "open":0.99925 }, "CHFUSD":{ "close":1.08098, "high":1.08884, "low":1.08041, "open":1.08579 }, "EURUSD":{ "close":1.08518, "high":1.0914, "low":1.08393, "open":1.08609 } }, "2023-01-31":{ "CHFEUR":{ "close":1.00489,…
Here is my dataframe: df year 2022 2021 0 return on equity (roe) 160.90% 144.10% 1 average equity 62027.9677 65704.372 2 net profit margin 0.2531 0.2588 3 turnover 1.1179 1.0422 4 leverage 5.687 5.3421 I want to write it into…