Iterate over column values in a dataframe – pandas

Question

I have a table like this

emp_id	emp_role	mgr_id	mgr_role
111	AP	112	SP
112	SP	116	DP
114	LP	115	DP

For each employee, I need to print the emp_role, his mgr_id and mgr_role

I have tried this

for id in df['emp_id']:
    print(id + 'with role' + df['emp_role'] + 'is reporting to' + df['mgr_id'] + 'with role' + df['mgr_role']

This prints the output multiple times but i need to print it exactly once. Please help to resolve this. Thanks in advance.

Expected output:

111 with role AP is reporting to 112 with role SP
112 with role SP is reporting to 116 with role DP
114 with role LP is reporting to 115 with role DP

Asked By: zoro

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Source

Answer 1

You can use the .iterrows() function to iterate through each row of the DataFrame and access the specific values for each column. Here is an example:

for index, row in df.iterrows():
    print(f"{row['emp_id']} with role {row['emp_role']} is reporting to {row['mgr_id']} with role {row['mgr_role']}")

This will iterate through each row of the DataFrame, and for each row, it will print the values of the "emp_id", "emp_role", "mgr_id", and "mgr_role" columns. You can also use f-strings instead of using ‘+’ to concatenate strings.

Answered By: Ivo Ribeiro

Answer 2

I think that you are really close to your approach. Depending on how you defined your table in Python, you can use print with format.

table = [    [111, "AP", 112, "SP"],
    [112, "SP", 116, "DP"],
    [114, "LP", 115, "DP"]
]

for row in table:
  emp_id, emp_role, mgr_id, mgr_role = row
  print("{} with role {} is reporting to {} with role {}".format(emp_id, emp_role, mgr_id, mgr_role))

Answered By: iohans

Iterate over column values in a dataframe – pandas

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