I have a simple dataframe and 2 string variables as below:
index col1
0 x
1 x
2 x
str1 = 'USD'
str2 = 'pricing'
I would like to rename the index to something like 'str1-str2-###':
index col1
USD-pricing-001 x
USD-pricing-002 x
USD-pricing-003 x
Any help is very much appreciated!
Use: DataFrame.add_prefix,
You also need use DataFrame.transpose beforehand because the add_prefix method acts on the columns. It is also necessary to use transpose at the end to return the dataframe to the original form
prefix=str1+'-'+str2+'-00'
df=df.set_index('index').T.add_prefix(prefix).T
print(df)
col1
index
USD-pricing-000 x
USD-pricing-001 x
USD-pricing-002 x
To respond to @razdi comment, to a more general solution, you would use:
prefix=str1+'-'+str2+'-'
df['index']=[(3-len(key))*'0'+key for key in df['index'].astype(str)]
df=df.set_index('index').T.add_prefix(prefix).T
print(df)
Example
df=pd.DataFrame()
df['col1']='x x x x x x x x x x x x x x'.split()
df.reset_index(inplace=True)
print(df)
index col1
0 0 x
1 1 x
2 2 x
3 3 x
4 4 x
5 5 x
6 6 x
7 7 x
8 8 x
9 9 x
10 10 x
11 11 x
12 12 x
13 13 x
Applying the code shown:
prefix=str1+'-'+str2+'-'
df['index']=[(3-len(key))*'0'+key for key in df['index'].astype(str)]
df=df.set_index('index').T.add_prefix(prefix).T
print(df)
col1
index
USD-pricing-000 x
USD-pricing-001 x
USD-pricing-002 x
USD-pricing-003 x
USD-pricing-004 x
USD-pricing-005 x
USD-pricing-006 x
USD-pricing-007 x
USD-pricing-008 x
USD-pricing-009 x
USD-pricing-010 x
USD-pricing-011 x
USD-pricing-012 x
USD-pricing-013 x
Of course this as long as your dataframe has less than 1000 lines.
### indicating only three digits are required in total. So the number of digits would need to change according to the indexAnother shorter way here
df = df.rename(lambda x: f'{str1}-{str2}-{x:003}')
Out[757]:
col1
index
USD-pricing-000 x
USD-pricing-001 x
USD-pricing-002 x
Try use listcomp, zip, and f-string to create list of joined string. Finally, assign it to df.index
arr = [f'{t[0]}-{t[1]}-{t[2]:03}' for t in
zip([str1] * df.index.size, [str2] * df.index.size, df.index)]
In [744]: arr
Out[744]: ['USD-pricing-000', 'USD-pricing-001', 'USD-pricing-002']
df.index = arr
Out[747]:
col1
USD-pricing-000 x
USD-pricing-001 x
USD-pricing-002 x
df = pd.DataFrame(\
{'col1': ['x' ,'x' ,'x' ,'x' ,'x'],\
},)
loops = len(df) + 1
list_index = []
for x in range(1,loops):
list_index.append("USD-pricing-00"+str(x))
df.index = list_index
Here is an easy to understand, single line solution:
df = pd.DataFrame({'col':['a',0]})
df.index = df.index.to_series().apply(lambda x: str(1) + '-' + str(2) + '-' + str(x).zfill(3))
Output:
>>> df
col
USD-pricing-000 a
USD-pricing-001 0
Using zfill avoids the issue of having index with numbers like 00100. Because you mentioned the format 'str1-str2-###', I'm assuming the number needs to be 3 digit. Using some of the previous formats, 00 will be fixed and will lead to 4 digit numbers with larger index values.
Figured out a way:
df['temp'] = str1 + '-' str2 + '-' + (df.index + 1).astype('str').str.zfill(3)
df.set_index('temp', inplace = True)
;)
