I use API, got many data but need to write only one to Pandas dataframe and then to csv file how can i do this? i need currency and rate columns only
import requests
import pandas as pd
url = 'https://api.apilayer.com/exchangerates_data/latest?base=EUR'
get_response = requests.get(url)
print(get_response.content)
reponse is
b'{\n "success": true,\n "timestamp": 1653291723,\n "base": "EUR",\n "date": "2022-05-23",\n "rates": {\n "AED": 3.891874,\n "AFN": 96.332724,\n "ALL": 120.12076,\n "AMD": 486.326147,\n "ANG": 1.910798,\n "AOA": 440.146399,\n "ARS": 125.559742,\n "AUD": 1.49136,\n "AWG": 1.907774,\n "AZN": 1.796984,\n "BAM": 1.958501,\n "BBD": 2.140687,\n "BDT": 92.747171,\n "BGN": 1.955884,\n "BHD": 0.399459,\n "BIF": 2179.202426,\n "BMD": 1.05958,\n "BND": 1.461113,\n "BOB": 7.300355,\n "BRL": 5.170217,\n "BSD": 1.060231,\n "BTC": 3.4686139e-05,\n "BTN": 82.245346,\n "BWP": 12.83561,\n "BYN": 3.578179,\n "BYR": 20767.765076,\n "BZD": 2.137314,\n "CAD": 1.355568,\n "CDF": 2124.457448,\n "CHF": 1.030337,\n "CLF": 0.032122,\n "CLP": 886.340415,\n "CNY": 7.067924,\n "COP": 4208.651167,\n "CRC": 711.74061,\n "CUC": 1.05958,\n "CUP": 28.078866,\n "CVE": 110.417129,\n "CZK": 24.584356,\n "DJF": 188.746891,\n "DKK": 7.440804,\n "DOP": 58.552672,\n "DZD": 154.438592,\n "EGP": 19.350685,\n "ERN": 15.893699,\n "ETB": 55.044138,\n "EUR": 1,\n "FJD": 2.284134,\n "FKP": 0.867087,\n "GBP": 0.843796,\n "GEL": 3.078048,\n "GGP": 0.867087,\n "GHS": 8.244159,\n "GIP": 0.867087,\n "GMD": 57.376242,\n "GNF": 9372.913662,\n "GTQ": 8.136894,\n "GYD": 221.832492,\n "HKD": 8.316976,\n "HNL": 26.044688,\n "HRK": 7.531387,\n "HTG": 118.758621,\n "HUF": 382.210602,\n "IDR": 15541.387462,\n "ILS": 3.544575,\n "IMP": 0.867087,\n "INR": 82.241939,\n "IQD": 1547.570278,\n "IRR": 44820.228002,\n "ISK": 138.696976,\n "JEP": 0.867087,\n "JMD": 163.866665,\n "JOD": 0.751235,\n "JPY": 135.279211,\n "KES": 123.494294,\n "KGS": 84.628222,\n "KHR": 4306.032696,\n "KMF": 494.770756,\n "KPW": 953.622101,\n "KRW": 1339.844028,\n "KWD": 0.324317,\n "KYD": 0.883605,\n "KZT": 451.435581,\n "LAK": 14057.368731,\n "LBP": 1603.386389,\n "LKR": 376.408573,\n "LRD": 161.585115,\n "LSL": 16.867967,\n "LTL": 3.128664,\n "LVL": 0.640929,\n "LYD": 5.0991,\n "MAD": 10.616176,\n "MDL": 20.305389,\n "MGA": 4285.919145,\n "MKD": 61.538618,\n "MMK": 1962.989296,\n "MNT": 3259.024764,\n "MOP": 8.570086,\n "MRO": 378.269824,\n "MUR": 45.988019,\n "MVR": 16.344051,\n "MWK": 866.149081,\n "MXN": 21.058086,\n "MYR": 4.645208,\n "MZN": 67.632728,\n "NAD": 16.868837,\n "NGN": 439.852629,\n "NIO": 37.997351,\n "NOK": 10.249848,\n "NPR": 131.573277,\n "NZD": 1.638153,\n "OMR": 0.40741,\n "PAB": 1.060346,\n "PEN": 3.9603,\n "PGK": 3.736248,\n "PHP": 55.384769,\n "PKR": 213.235927,\n "PLN": 4.617629,\n "PYG": 7251.300917,\n "QAR": 3.857965,\n "RON": 4.946967,\n "RSD": 117.499439,\n "RUB": 62.329807,\n "RWF": 1088.946708,\n "SAR": 3.974436,\n "SBD": 8.607563,\n "SCR": 14.438411,\n "SDG": 473.497309,\n "SEK": 10.486142,\n "SGD": 1.457722,\n "SHP": 1.459462,\n "SLL": 13581.160767,\n "SOS": 618.272012,\n "SRD": 22.260709,\n "STD": 21931.163629,\n "SVC": 9.277651,\n "SYP": 2662.141945,\n "SZL": 16.788471,\n "THB": 36.311502,\n "TJS": 13.261298,\n "TMT": 3.708529,\n "TND": 3.243904,\n "TOP": 2.459973,\n "TRY": 16.843815,\n "TTD": 7.198816,\n "TWD": 31.379439,\n "TZS": 2464.582977,\n "UAH": 31.322712,\n "UGX": 3864.924954,\n "USD": 1.05958,\n "UYU": 42.945451,\n "UZS": 11764.462107,\n "VEF": 226570195087.7927,\n "VND": 24545.167244,\n "VUV": 121.073594,\n "WST": 2.73302,\n "XAF": 656.781309,\n "XAG": 0.048294,\n "XAU": 0.000571,\n "XCD": 2.863568,\n "XDR": 0.790993,\n "XOF": 656.781309,\n "XPF": 120.315233,\n "YER": 265.159952,\n "ZAR": 16.77781,\n "ZMK": 9537.495082,\n "ZMW": 18.060768,\n "ZWL": 341.18428\n }\n}\n'
CodePudding user response：
first load data as DataFrame
import json
df = json.loads(get_response.content)
second, choose the rates (currency is index) and save to csv
df[["base","rates"]].to_csv("path/to/csv")
cheers :)
CodePudding user response：
import requests
import pandas as pd
import json
url = 'https://api.apilayer...'
get_response = requests.get(url)
# Parse the response to a dict
response_dict = get_response.json()
# Turn the rates nodes into a dataframe
data_items = response_dict['rates'].items()
data_list = list(data_items)
df = pd.DataFrame(data_list,columns=['currency','rate'])
# Export to csv
df.to_csv('export.csv')
CodePudding user response：
IIUC, you can use:
import json
df = pd.DataFrame(json.loads(get_response.content.decode('utf-8')))[['base', 'rates']]
# for export to csv
# df.to_csv('filename.csv')
output:
base rates
AED EUR 3.893237
AFN EUR 96.366461
ALL EUR 120.162829
AMD EUR 486.496485
ANG EUR 1.911467
.. ... ...
YER EUR 265.252922
ZAR EUR 16.796411
ZMK EUR 9540.830787
ZMW EUR 18.067093
ZWL EUR 341.303769
[168 rows x 2 columns]
CodePudding user response：
get_response = requests.get(url)
# print(get_response.content)
in_json = get_response.json()
# print(in_json)
fd = pd.DataFrame(in_json)
y = fd[['rates']]
print(y)
solved but looks not nice and maybe there a more simple solution i converted to json - then to dataframe - then i will convert to csv