过滤 csv 表，使其只有 2 列。 Python 熊猫 pd .pd答案

【问题标题】：FIlrer csv table to have just 2 columns. Python pandas pd .pd过滤 csv 表，使其只有 2 列。 Python 熊猫 pd .pd
【发布时间】：2022-12-06 09:05:28
【问题描述】：

我得到了 .csv 文件，其中包含这样的行：

result,table,_start,_stop,_time,_value,_field,_measurement,device
,0,2022-10-23T08:22:04.124457277Z,2022-11-22T08:22:04.124457277Z,2022-10-24T12:12:35Z,44.61,power,shellies,Shelly_Kitchen-C_CoffeMachine/relay/0
,0,2022-10-23T08:22:04.124457277Z,2022-11-22T08:22:04.124457277Z,2022-10-24T12:12:40Z,17.33,power,shellies,Shelly_Kitchen-C_CoffeMachine/relay/0
,0,2022-10-23T08:22:04.124457277Z,2022-11-22T08:22:04.124457277Z,2022-10-24T12:12:45Z,41.2,power,shellies,Shelly_Kitchen-C_CoffeMachine/relay/0
,0,2022-10-23T08:22:04.124457277Z,2022-11-22T08:22:04.124457277Z,2022-10-24T12:12:51Z,33.49,power,shellies,Shelly_Kitchen-C_CoffeMachine/relay/0
,0,2022-10-23T08:22:04.124457277Z,2022-11-22T08:22:04.124457277Z,2022-10-24T12:12:56Z,55.68,power,shellies,Shelly_Kitchen-C_CoffeMachine/relay/0
,0,2022-10-23T08:22:04.124457277Z,2022-11-22T08:22:04.124457277Z,2022-10-24T12:12:57Z,55.68,power,shellies,Shelly_Kitchen-C_CoffeMachine/relay/0
,0,2022-10-23T08:22:04.124457277Z,2022-11-22T08:22:04.124457277Z,2022-10-24T12:13:02Z,25.92,power,shellies,Shelly_Kitchen-C_CoffeMachine/relay/0
,0,2022-10-23T08:22:04.124457277Z,2022-11-22T08:22:04.124457277Z,2022-10-24T12:13:08Z,5.71,power,shellies,Shelly_Kitchen-C_CoffeMachine/relay/0

我需要让它们看起来像这样：

                   time  value
0  2022-10-24T12:12:35Z  44.61
1  2022-10-24T12:12:40Z  17.33
2  2022-10-24T12:12:45Z  41.20
3  2022-10-24T12:12:51Z  33.49
4  2022-10-24T12:12:56Z  55.68

我的异常检测代码需要它，这样我就不必手动删除列等。至少不是全部。我无法使用与收集瓦数信息的机器配合使用的程序来做到这一点。我试过了，但它不够用：

df = pd.read_csv('coffee_machine_2022-11-22_09_22_influxdb_data.csv')
df['_time'] = pd.to_datetime(df['_time'], format='%Y-%m-%dT%H:%M:%SZ')
df = pd.pivot(df, index = '_time', columns = '_field', values = '_value')
df.interpolate(method='linear') # not neccesary

它给出了这个输出：

            0
9      83.908
10     80.342
11     79.178
12     75.621
13     72.826
...       ...
73522  10.726
73523   5.241

【问题讨论】：

标签： python pandas csv anomaly-detection isolation-forest

【解决方案1】：

这是向下投影到 pandas 生态系统中列子集的规范方法。

df = df[['_time', '_value']]

【讨论】：

【解决方案2】：

以下是如何执行此操作的示例：

import pandas as pd

# Read the CSV file into a pandas DataFrame
df = pd.read_csv('coffee_machine_2022-11-22_09_22_influxdb_data.csv')

# Convert the _time column to a datetime type
df['_time'] = pd.to_datetime(df['_time'], format='%Y-%m-%dT%H:%M:%SZ')

# Drop the columns that you don't need
df = df.drop(columns=['result', 'table', '_start', '_stop', '_field', '_measurement', 'device'])

# Set the index of the DataFrame to the _time column
df = df.set_index('_time')

# Print the resulting DataFrame
print(df)

此代码将 CSV 文件读入 pandas DataFrame，将 _time 列转换为 datetime 类型，删除不需要的列，将 DataFrame 的索引设置为 _time 列，然后打印生成的 DataFrame。

您可以修改此代码以满足您的特定需要和要求。例如，您可以使用 interpolate 方法来填充 _value 列中的缺失值，或者您可以使用 resample 方法将数据重新采样到不同的时间间隔。

【讨论】：