使用pandas to_csv将结果写入csv

debugcn 发表于 Dev

sree

下面是我的代码，该代码从excel工作表获取实例名称，并在aws帐户中搜索实例名称并获取实例ID。因此，该过程运行良好。现在我想将数据写入csv，就像在csv中一样，必须有两列，其名称必须如instancename和instanceId，并且数据应打印在相应的列中。请帮助我获得所需的输出。csv与数据重叠，一旦打开csv，我只能看到其中的最后一个值，因为我的脚本会覆盖以前的结果。

import pandas as pd
from pandas import ExcelWriter
from pandas import ExcelFile
import numpy as np
import os
import boto3
client = boto3.client('ec2')
THIS_FOLDER = os.path.dirname(os.path.abspath(__file__))
my_file = os.path.join(THIS_FOLDER, 'example.xlsx')

df = pd.read_excel(my_file, sheet_name='Sheet2')

list1 = df['EC2NAMES']
print(list1)
client = boto3.client('ec2')
for names in list1:
    custom_filter = [{
        'Name':'tag:Name', 
        'Values': [names]}]
    print(names)
    instances = client.describe_instances(Filters=custom_filter)
    for instance in instances['Reservations']:
        for key in instance["Instances"]:
            x = key['InstanceId']
            print(x)
            data = pd.DataFrame({'A' : [names],'B' : [x]})
            data.to_csv('df111111.csv')

预期产量：

Instancename  InstanceID
testinstance  123456
testinstance1 12345656312
testinstance2 12345657237

实际输出：

Instancename  InstanceID
testinstance2 12345657237

Poojan

您可以使用熊猫，concat或者append最好的方法是将数据存储到列表中，最后创建一个数据框并将其另存为csv。

import pandas as pd
from pandas import ExcelWriter
from pandas import ExcelFile
import numpy as np
import os
import boto3
client = boto3.client('ec2')
THIS_FOLDER = os.path.dirname(os.path.abspath(__file__))
my_file = os.path.join(THIS_FOLDER, 'example.xlsx')

df = pd.read_excel(my_file, sheet_name='Sheet2')

list1 = df['EC2NAMES']
print(list1)
client = boto3.client('ec2')
data = []
for names in list1:
    custom_filter = [{
        'Name':'tag:Name', 
        'Values': [names]}]
    print(names)
    instances = client.describe_instances(Filters=custom_filter)
    for instance in instances['Reservations']:
        for key in instance["Instances"]:
            x = key['InstanceId']
            print(x)
            data.append([names, x])
pd.DataFrame(data, colums=['A','B']).to_csv('df111111.csv')

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