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@smijar
Last active November 17, 2022 15:19
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Using pandas to read CSV and convert each row into a dictionary
canadacentral env-1 demogroup-1
westus env-2 demogroup-1
westus env-3 demogroup-1
westus env-4 demogroup-1
westus env-5 demogroup-1
uksouth env-1 demogroup-2
canadacentral env-2 demogroup-2
canadacentral env-3 demogroup-2
canadacentral env-4 demogroup-2
canadacentral env-5 demogroup-2
westeurope env-1 demogroup-3
westeurope env-2 demogroup-3
westeurope env-3 demogroup-3
westeurope env-4 demogroup-3
westeurope env-5 demogroup-3
northeurope env-1 demogroup-4
northeurope env-2 demogroup-4
northeurope env-3 demogroup-4
northeurope env-4 demogroup-4
northeurope env-5 demogroup-4
eastus env-1 demogroup-5
eastus env-2 demogroup-5
eastus env-3 demogroup-5
eastus env-4 demogroup-5
eastus env-5 demogroup-5
eastus2 env-1 demogroup-6
eastus2 env-2 demogroup-6
eastus2 env-3 demogroup-6
eastus2 env-4 demogroup-6
eastus2 env-5 demogroup-6
eastasia env-1 demogroup-7
eastasia env-2 demogroup-7
eastasia env-3 demogroup-7
eastasia env-4 demogroup-7
eastasia env-5 demogroup-7
australiaeast env-1 demogroup-8
australiaeast env-2 demogroup-8
australiaeast env-3 demogroup-8
australiaeast env-4 demogroup-8
australiaeast env-5 demogroup-8
germanywestcentral env-1 demogroup-9
germanywestcentral env-2 demogroup-9
germanywestcentral env-3 demogroup-9
germanywestcentral env-4 demogroup-9
germanywestcentral env-5 demogroup-9
japaneast env-1 demogroup-10
japaneast env-2 demogroup-10
japaneast env-3 demogroup-10
japaneast env-4 demogroup-10
japaneast env-5 demogroup-10
import pandas as pd
df = pd.read_csv('envs.txt', sep='\s+', header=None)
# print(df)
#df.to_csv('envs.csv', header=None)
# for row in df.iterrows():
# print(row[0], row[1])
rows = []
for i in range(0, len(df)):
# print(df.iloc[i][0], df.iloc[i][1], df.iloc[i][2])
rows.append({'location': df.iloc[i][0], 'env': df.iloc[i][1], 'group': df.iloc[i][2]})
for row in rows:
print(row['location'], row['env'], row['group'])
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