对于每行重复，请使用：df = pd.DataFrame(data = {'Name':['Tom', 'Jerry', 'Jack', 'Terry'],

'OtherName':['Tom', 'John', 'Bob','Steve'],

'Age':[20, 21, 19, 18]})

print (df)

Name OtherName Age

0 Tom Tom 20

1 Jerry John 21

2 Jack Bob 19

3 Terry Steve 18

import inflect

p = inflect.engine()

#map by function for dynamic counter

f = lambda i: p.number_to_words(p.ordinal(i))

#columns filled by names

cols = ['Name','OtherName']

#reshaped to MultiIndex Series

s = df[cols].stack()

#counter per groups

count = s.groupby([s.index.get_level_values(0),s]).cumcount().add(1)

#mask for filter duplicates

mask = s.reset_index().duplicated(['level_0',0], keep=False).values

#filter only duplicates and map, reshape back and add to original data

df[cols] = count[mask].map(f).unstack().add(df[cols], fill_value='')

print (df)

Name OtherName Age

0 firstTom secondTom 20

1 Jerry John 21

2 Jack Bob 19

3 Terry Steve 18data = {'Name':['Tom', 'Tom', 'Jack', 'Terry'], 'Age':[20, 21, 19, 18]}

df = pd.DataFrame(data)

nth = {

0:"First",

1:"Second",

2:"Third",

3:"Fourth"

}

mask = df.Name.duplicated(keep=False)

df.loc[mask, 'Name'] = df[mask].groupby('Name').cumcount().map(nth) + df.loc[mask, 'Name']

print (df)

Name Age

0 FirstTom 20

1 SecondTom 21

2 Jack 19

3 Terry 18

动态字典应类似于：import inflect

p = inflect.engine()

mask = df.Name.duplicated(keep=False)

f = lambda i: p.number_to_words(p.ordinal(i))

df.loc[mask, 'Name'] = df[mask].groupby('Name').cumcount().add(1).map(f) + df.loc[mask, 'Name']

print (df)

Name Age

0 firstTom 20

1 secondTom 21

2 Jack 19

3 Terry 18