问题
I have a csv with two columns: employee id 'eid'
and manager's employee id 'mid'
. Trying to get python code that will, for each employee, add columns showing employee id's of the manager all the way to CEO. CEO has a an employee id of 1. Ultimately I want to write the result back to a csv.
So the data looks like:
eid, mid
111, 112
113, 112
112, 114
114, 115
115, 1
I am expecting output that looks like this. Note that while no employee will have more than 4 levels of managers, but i would like to also learn python that names columns dynamically.
eid, mid, l2mid l3mid l4mid
111, 112, 114, 115, 1
113, 112, 114, 115, 1
112, 114, 115, 1
114, 115, 1
115, 1
I am very new to coding, and trying to teach myself but keep getting stuck. My questions:
1) I was trying to use a for statement that took mid
in a given row, then found that that manager's manager, and so on, until i reached the CEO. I have been trying along these lines:
df = pd.read_csv('employee.csv')
if mid =! 1
for i in df:
df.['l2mid'] = df.loc[df.eid == [i], [mid]]
Maybe I'm approaching this backwards and I should try grouping all employees by manager? How would that code be different?
I have seen solutions in C# and sql, and i've seen solutions that build trees and json. I really appreciate any help and encouragement.
Update: next step was to add a country column - see: entry here
回答1:
I believe there is a better solution, but this works. I filled empty with zeros.
a = []
for index, row in df.iterrows():
res = df[df['eid']==row['mid']]['mid'].values
a.append(0 if not res else res[0])
df['l2mid'] = a
a = []
for index, row in df.iterrows():
res = df[df['eid']==row['l2mid']]['mid'].values
a.append(0 if not res else res[0])
df['l3mid'] = a
a = []
for index, row in df.iterrows():
res = df[df['eid']==row['l3mid']]['mid'].values
a.append(0 if not res else res[0])
df['l4mid'] = a
df
# output :
# eid mid l2mid l3mid l4mid
# 0 111 112 114 115 1
# 1 113 112 114 115 1
# 2 112 114 115 1 0
# 3 114 115 1 0 0
# 4 115 1 0 0 0
You can define a function for routines.
def search_manager(target_column, new_column):
a = []
for index, row in df.iterrows():
res = df[df['eid']==row[target_column]]['mid'].values
a.append(0 if not res else res[0])
df[new_column] = a
search_manager('mid', 'l2mid')
search_manager('l2mid', 'l3mid')
search_manager('l3mid', 'l4mid')
来源:https://stackoverflow.com/questions/45929048/python-hierarchy-from-manager-and-employee-id