Reputation: 13
I want to convert my data that is in this form to YAML Syntax (preferably without using pandas or need to install new libraries)
Sample data in excel :
users | name | uid | shell
user1 | nino | 8759 | /bin/ksh
user2 | vivo | 9650 | /bin/sh
Desired output format : YAML Syntax output
Upvotes: 1
Views: 11923
Reputation: 864
You can do it using file operations. Since you are keen on *"preferably without using pandas or need to install new libraries
Assumption : The "|" symbol is to indicate columns and is not a delimiter or separater
Save the excel file as CSV
Then run the code
# STEP 1 : Save your excel file as CSV
ctr = 0
excel_filename = "Book1.csv"
yaml_filename = excel_filename.replace('csv', 'yaml')
users = {}
with open(excel_filename, "r") as excel_csv:
for line in excel_csv:
if ctr == 0:
ctr+=1 # Skip the coumn header
else:
# save the csv as a dictionary
user,name,uid,shell = line.replace(' ','').strip().split(',')
users[user] = {'name': name, 'uid': uid, 'shell': shell}
with open(yaml_filename, "w+") as yf :
yf.write("users: \n")
for u in users:
yf.write(f" {u} : \n")
for k,v in users[u].items():
yf.write(f" {k} : {v}\n")
users:
user1 :
name : nino
uid : 8759
shell : /bin/ksh
user2 :
name : vivo
uid : 9650
shell : /bin/sh
Upvotes: 1
Reputation: 7594
You can do this, in your case you would just do pd.read_excel
instead of pd.read_csv
:
df = pd.read_csv('test.csv', sep='|')
df['user_col'] = 'users'
data = df.groupby('user_col')[['users', 'name','uid','shell']].apply(lambda x: x.set_index('users').to_dict(orient='index')).to_dict()
with open('newtree.yaml', "w") as f:
yaml.dump(data, f)
Yaml file looks like this:
users:
user1:
name: nino
shell: /bin/ksh
uid: 8759
user2:
name: vivo
shell: /bin/sh
uid: 9650
Upvotes: 0