删除特定字符后的所有字符，而不是字符本身，在整列中，python

Question

I have a data frame that I made into a dict for reproducibility purposes. I want to delete all characters after the last "1" in the "index" column, not deleting "1" itself. Does someone know how to quickly do this? I tried the following but it also deleted the "1":

df1['index'] = [x.split('1')[-1] for x in df1['index']]

{0: {'1': 0.001549586776859504,
  '10': 0.001549586776859504,
  '11': 0.00017217630853994488,
  '12': 4.304407713498622e-05,
  '13': 0.00012913223140495865},
 1: {'1': 0.000387396694214876,
  '10': 0.000387396694214876,
  '11': nan,
  '12': nan,
  '13': nan},
 2: {'1': 0.001162190082644628,
  '10': 0.001162190082644628,
  '11': 9.838646202282564e-05,
  '12': 2.459661550570641e-05,
  '13': 7.378984651711923e-05},
 3: {'1': 0.015883264462809916,
  '10': 0.015883264462809916,
  '11': 0.0006149153876426602,
  '12': 0.00015372884691066505,
  '13': 0.0004611865407319952},
 4: {'1': 0.00387396694214876,
  '10': 0.00387396694214876,
  '11': 0.00012298307752853205,
  '12': 3.0745769382133014e-05,
  '13': 9.223730814639904e-05},
 5: {'1': 0.001549586776859504,
  '10': 0.001549586776859504,
  '11': nan,
  '12': nan,
  '13': nan},
 6: {'1': 0.005423553719008264,
  '10': 0.005423553719008264,
  '11': 0.0002951593860684769,
  '12': 7.378984651711923e-05,
  '13': 0.00022136953955135768},
 7: {'1': 0.001549586776859504,
  '10': 0.001549586776859504,
  '11': 0.00017217630853994488,
  '12': 4.304407713498622e-05,
  '13': 0.00012913223140495865},
 8: {'1': 0.001162190082644628,
  '10': 0.001162190082644628,
  '11': nan,
  '12': nan,
  '13': nan},
 9: {'1': 0.001549586776859504,
  '10': 0.001549586776859504,
  '11': 7.378984651711923e-05,
  '12': 1.8447461629279807e-05,
  '13': 5.534238488783942e-05},
 'index': {'1': '00', '10': '000', '11': '0', '12': '20', '13': '30'}}

Answer 1

this solution convert int to string then search for first number different number from zero then take the partition you need (from begining to the position of the number different from zero) and convert it back to float. happy coding

df1['index']=[float(x[:x.find(x.split(".")[-1].replace("0","")[0])+1]) for x in list(map(str,df1['index']))]