如何使用python可视化从grafana导出csv数据

Question

When i export csv data from grafana with API latency i saw two kind of value is seconds and millisecond, how to convert it to seconds using python.

time                 latency    
2022-09-30 06:20:00  957 ms
2022-09-30 07:25:00  6.63 s
2022-09-30 07:30:00  634 ms

More thing, with csv how i can visualize this data using python. plz

Answer 1

You can upload all the csv data into a pandas dataframe (you would use pd.read_csv() for this. From this you can use the df.apply() method to convert the seconds into miliseconds.

The df.apply() calls the user defined convert() function and you can see how that splits the latency column into numbers and strings .

This would work:

import io
import pandas as pd


x = '''
time                 latency    
2022-09-30 06:20:00  957 ms
2022-09-30 07:25:00  6.63 s
2022-09-30 07:30:00  634 ms

'''

data = io.StringIO(x)

df = pd.read_csv(data, sep='\s\s+', engine='python')

def convert(x:str):
    ''' convert string to number ms'''
    a, b = x.split(' ')
    a = float(a)
    if b =='s':
        a = a*1000
    return a

df['ms'] = df['latency'].apply(convert)
df

result

                 time latency      ms
0  2022-09-30 06:20:00  957 ms   957.0
1  2022-09-30 07:25:00  6.63 s  6630.0
2  2022-09-30 07:30:00  634 ms   634.0