我有一个从InfluxDB UI
下载的CSV
文件。我想从下载的文件中提取有用的数据。下载文件的片段如下:
#group FALSE FALSE TRUE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE
#datatype string long dateTime:RFC3339 dateTime:RFC3339 dateTime:RFC3339 double string string string string string
#default mean
result table _start _stop _time _value _field _measurement smart_module serial type
0 2023-03-31T08:12:40.697076925Z 2023-03-31T09:12:40.697076925Z 2023-03-31T08:20:00Z 0 sm_alarm system_test 8 2.14301E+11 sm_extended
0 2023-03-31T08:12:40.697076925Z 2023-03-31T09:12:40.697076925Z 2023-03-31T08:40:00Z 0 sm_alarm system_test 8 2.14301E+11 sm_extended
0 2023-03-31T08:12:40.697076925Z 2023-03-31T09:12:40.697076925Z 2023-03-31T09:00:00Z 0 sm_alarm system_test 8 2.14301E+11 sm_extended
0 2023-03-31T08:12:40.697076925Z 2023-03-31T09:12:40.697076925Z 2023-03-31T09:12:40.697076925Z 0 sm_alarm system_test 8 2.14301E+11 sm_extended
我希望输出CSV如下:
_time sm_alarm next_column next_column ....... ...........
2023-03-29T08:41:15Z 0
请注意,sm_alarm
只是其他9个字段(在_filed
下)中的一个字段。
我尝试使用以下脚本,但无法解决我的问题。
import csv
# Specify the input and output file names
input_file = 'influx.csv'
output_file = 'output.csv'
try:
# Open the input file for reading
with open(input_file, 'r') as csv_file:
# Create a CSV reader object
csv_reader = csv.reader(csv_file)
# Skip the first row (header)
next(csv_reader)
# Open the output file for writing
with open(output_file, 'w', newline='') as output_csv:
# Create a CSV writer object
csv_writer = csv.writer(output_csv)
# Write the header row
csv_writer.writerow(['_time', '_field', '_value'])
# Iterate over the input file and write the rows to the output file
for row in csv_reader:
# Check if the row is not empty
if row:
# Split the fields
fields = row[0].split(',')
# Write the row to the output file
csv_writer.writerow(fields)
print(f'{input_file} converted to {output_file} successfully!')
except FileNotFoundError:
print(f'Error: File {input_file} not found.')
except Exception as e:
print(f'Error: {e}')
谢谢大家。
1条答案
按热度按时间qij5mzcb1#
预期输出的格式不明确且不完全清楚。
但是作为一个 * 起点 *,你可以用
read_csv
从pandas中理顺你的文件:输出: