I am using Rest API. I need data in the form of a data frame. For this, I am using pandas. The query parameter of Rest API is connected to Database, so I am getting multiple outputs from Rest API. I want to merge these outputs in the same data frame. Anyone can help me ?
cur.execute("SELECT * from curd")
rows = cur.fetchall()
l = []
for row in rows:
#print("ID = ", row[1], "\n")
r = requests.get("http://localhost:8280/ID=" row[1], headers={uniquestr('Authorization'): 'Basic ',uniquestr('Authorization'): 'Basic'})
#print("CONSUMER_ID = ", row[1], "\n")
s = r.json()
df = pd.DataFrame(s['R']['L'])
df1 = df.groupby(pd.to_datetime(df.DateTime).dt.date).agg({'ACT': 'sum'}).reset_index()
and Code output is
DateTime ACT_IMP_TOT
0 2022-05-01 19.252
1 2022-05-02 19.911
2 2022-05-03 23.671
DateTime ACT_IMP_TOT
0 2022-05-01 37.352
1 2022-05-02 27.780
2 2022-05-03 28.557
CodePudding user response:
So:
dfs = []
cur.execute("SELECT * from curd")
rows = cur.fetchall()
l = []
for row in rows:
#print("ID = ", row[1], "\n")
r = requests.get("http://localhost:8280/ID=" row[1], headers={uniquestr('Authorization'): 'Basic ',uniquestr('Authorization'): 'Basic'})
#print("CONSUMER_ID = ", row[1], "\n")
s = r.json()
df = pd.DataFrame(s['R']['L'])
df1 = df.groupby(pd.to_datetime(df.DateTime).dt.date).agg({'ACT': 'sum'}).reset_index()
dfs.append(df1)
print(pd.concat(dfs))