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')
预期输出:
Instancename InstanceID
testinstance 123456
testinstance1 12345656312
testinstance2 12345657237
实际输出:
Instancename InstanceID
testinstance2 12345657237
答案 0 :(得分:2)
您可以使用熊猫concat
或append
,但最好的方法是将数据存储到列表中,最后制作一个数据框并将其保存为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')
答案 1 :(得分:1)
您的代码为for循环的每次迭代创建一个新的“数据”变量。我的尝试是在开始循环之前制作一个空白数据变量。在每个循环中向数据帧添加一个新片段,一旦退出循环,将其保存到csv
data = pd.DataFrame()
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 = data.append(pd.DataFrame({'A' : [names],'B' : [x]}))
data.to_csv('df111111.csv')