I have a Influx Bucket where I want to upload a predictions time series dataset for each id_number, the predictions for each goes 2 months in the future. The thing is that everytime I try to upload it with the Influx UI it return me the error: "Failed to upload the selected CSV: error in csv.from(): failed to read metadata: failed to read header row: wrong number of fields" The dataset looks like this: #datatype,dateTime:RFC3339,double,string #group,false,false,false #default,,, date,trend,id_Number 2024-05-24T00:00:00Z,142.49524140527743,159345 2024-05-25T00:00:00Z,143.06121931128922,159345 2024-05-26T00:00:00Z,143.62719721730102,159345 2024-05-27T00:00:00Z,144.1931751233128,159345 2024-05-28T00:00:00Z,144.75915302932464,159345 2024-05-29T00:00:00Z,145.32513095717914,159345 2024-05-30T00:00:00Z,145.89110888503367,159345 2024-05-31T00:00:00Z,146.45708681288818,159345 2024-06-01T00:00:00Z,147.02306474074268,159345 Besides that I trying to create an script in python to upload the file into a bucket but everytime i try it the data is not uploaded unless I delete the ".time(iso_timestamp)" def write_dataframe(self, df: pd.DataFrame, measurement: str, tag_columns: Optional = None): if tag_columns is None: tag_columns = ["id_Number"] required_columns = {"date", "trend", "id_Number"} points = [] for _, row in df.iterrows(): meter_number = str(row["id_Number"]) if pd.notna(row["id_Number"]) else "unknown" trend = float(row["trend"]) timestamp = row["date"] if pd.isna(timestamp): print(f"Skipping row due to invalid timestamp: {row['date']}") continue iso_timestamp = timestamp.isoformat() point = ( Point(measurement) .tag("id_Number", meter_number) .field("trend", trend) .time(iso_timestamp) ) points.append(point) Any thoughts would be greatly appreciated. Thanks. Continue reading...
