Hugging Face's logo

Spaces:
srishtichugh
/
orgOS
Running

App Files Community
orgOS
File size: 28,056 Bytes
4719066
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
��python : Data Cleaning OpenEnv -- Baseline Inference

At line:1 char:1

+ python inference.py 2>&1 | Tee-Object -FilePath inference_log.txt

+ ~~~~~~~~~~~~~~~~~~~~~~~~

    + CategoryInfo          : NotSpecified: (Data Cleaning O...eline Inference: 

   String) [], RemoteException

    + FullyQualifiedErrorId : NativeCommandError

 

Model : google/gemma-3-27b-it

Env   : http://localhost:8000

Health check: OK





============================================================

  Running Task 1

============================================================

[START] task=data-cleaning-task1 env=data-cleaning-openenv model=google/gemma-3-27b-it

  Step  1 | score=0.0100 | action={"operation":"fill_missing","column":"age","pa

rams":{"strategy":"median"}}

           -> Filled 20 missing values in 'age' using median.

[STEP] step=1 action={"operation":"fill_missing","column":"age","params":{"strategy":"median"}} reward=0.39 done=false error=null

  Step  2 | score=0.4000 | action={"operation":"fill_missing","column":"salary",

"params":{"strategy":"median"}}

           -> Filled 20 missing values in 'salary' using median.

[STEP] step=2 action={"operation":"fill_missing","column":"salary","params":{"strategy":"median"}} reward=0.40 done=false error=null

  Step  3 | score=0.8000 | action={"operation":"fill_missing","column":"departme

nt","params":{"strategy":"mode"}}

           -> Filled 10 missing values in 'department' using mode.

[STEP] step=3 action={"operation":"fill_missing","column":"department","params":{"strategy":"mode"}} reward=0.19 done=true error=null

[END] task=data-cleaning-task1 score=0.9900 steps=3



  Task 1 final score: 0.9900  (steps used: 3)



============================================================

  Running Task 2

============================================================

[START] task=data-cleaning-task2 env=data-cleaning-openenv model=google/gemma-3-27b-it

  Step  1 | score=0.0100 | action={"operation":"drop_duplicates"}

           -> Dropped 15 duplicate rows.

[STEP] step=1 action={"operation":"drop_duplicates"} reward=0.34 done=false error=null

  Step  2 | score=0.3501 | action={"operation":"fix_format","column":"phone"}

           -> Fixed 74 phone numbers in 'phone' to NNN-NNN-NNNN format.

[STEP] step=2 action={"operation":"fix_format","column":"phone"} reward=0.32 done=false error=null

  Step  3 | score=0.6739 | 

action={"operation":"fix_format","column":"listed_date"}

           -> Fixed 82 dates in 'listed_date' to YYYY-MM-DD format.

[STEP] step=3 action={"operation":"fix_format","column":"listed_date"} reward=0.32 done=true error=null

[END] task=data-cleaning-task2 score=0.9900 steps=3



  Task 2 final score: 0.9900  (steps used: 3)



============================================================

  Running Task 3

============================================================

[START] task=data-cleaning-task3 env=data-cleaning-openenv model=google/gemma-3-27b-it

  Step  1 | score=0.0100 | action={"operation":"fill_missing","column":"age","pa

rams":{"strategy":"median"}}

           -> Filled 52 missing values in 'age' using median.

[STEP] step=1 action={"operation":"fill_missing","column":"age","params":{"strategy":"median"}} reward=0.07 done=false error=null

  Step  2 | score=0.0807 | action={"operation":"fill_missing","column":"purchase

_amount","params":{"strategy":"mean"}}

           -> Filled 46 missing values in 'purchase_amount' using mean.

[STEP] step=2 action={"operation":"fill_missing","column":"purchase_amount","params":{"strategy":"mean"}} reward=0.07 done=false error=null

  Step  3 | score=0.1522 | action={"operation":"fill_missing","column":"country"

,"params":{"strategy":"mode"}}

           -> Filled 32 missing values in 'country' using mode.

[STEP] step=3 action={"operation":"fill_missing","column":"country","params":{"strategy":"mode"}} reward=0.05 done=false error=null

  Step  4 | score=0.2019 | action={"operation":"fill_missing","column":"signup_d

ate","params":{"strategy":"median"}}

           -> Operation failed: Cannot convert [nan '2022-12-15' '2023-12-20' 

nan '2023-04-21' '2023-10-22' nan

 '2023-06-11' '2022-07-27' '2023-12-05' '2023-04-01' '2023-07-25'

 '2022-12-03' '2023-09-25' '24/02/2022' '2022-03-25' 'Jan 06 2023'

 '2023-06-19' '2023-08-14' '2022-11-18' '2023-04-20' '2023-02-08'

 'Dec 03 2023' '2023-04-23' '01/11/2022' '2023-12-09' 'Mar 20 2022' nan

 '23/04/2022' '2022-07-30' '2023-08-23' '2023-06-20' '2023-12-10'

 '2023-07-02' '2023-04-11' '2022-09-10' '2022-01-04' '2022-04-01'

 '2022-08-06' '2022-01-30' '2023-01-06' '2023-07-22' '2023-12-05'

 '24/12/2022' '2023-10-01' '21/12/2023' '2023-09-20' '2022-12-06'

[STEP] step=4 action={"operation":"fill_missing","column":"signup_date","params":{"strategy":"median"}} reward=0.01 done=false error=null

 '2022-08-26' '15/12/2023' '2022-06-26' '2022-10-28' '2022-02-24'

 '2023-08-03' '2023-04-20' nan '2022-06-12' '2023-02-10' nan '2023-08-09'

 '2022-07-14' '07/11/2023' 'Nov 21 2022' '2023-08-24' '2022-06-24'

 '2022-01-27' '2022-02-10' 'Sep 30 2022' '2023-11-27' 'Feb 05 2022'

 'Sep 27 2022' 'Mar 21 2022' '2023-11-12' 'May 08 2023' '2023-07-11'

 '2023-06-05' '2023-04-25' '2023-07-19' '2022-01-06' '2023-09-24'

 'Jun 25 2023' '24/06/2023' '15/10/2022' '2023-08-08' '2022-10-06'

 'Feb 05 2022' 'Oct 25 2023' '21/06/2022' 'Mar 16 2022' '2023-03-30'

 '2022-06-20' '2023-09-19' nan '2022-01-04' '2023-11-26' '2023-01-11'

 '11/07/2022' '2023-05-10' '2023-01-23' '2022-01-22' nan '2022-10-20'

 'May 26 2023' '2023-10-16' 'Mar 22 2023' nan '2022-07-05' '2022-06-23'

 '2022-10-30' '2023-09-15' '2023-01-18' '2022-09-12' '24/07/2023' nan

 '2023-10-21' '2022-08-07' 'Jun 03 2023' 'Mar 07 2023' nan '2022-10-17'

 nan '20/07/2022' '2023-02-06' 'Oct 10 2023' 'Sep 25 2023' nan

 '2023-05-11' '2022-03-03' '2023-05-08' '2022-09-07' '2022-11-25'

 '2023-06-08' 'Nov 07 2022' 'Aug 13 2023' '2023-01-25' '2023-12-31'

 '2023-04-11' '05/08/2022' '2023-07-20' '2022-10-25' '2023-01-25'

 'Apr 10 2022' '29/03/2022' '2023-02-24' '17/05/2022' '2023-12-30'

 '2023-09-17' 'May 27 2023' '2023-06-21' '2023-03-11' 'Feb 14 2022' nan

 '28/12/2022' '31/10/2023' '2022-06-10' '2022-12-29' '2022-09-09'

 'Apr 09 2022' '2022-03-17' '2022-09-24' '02/03/2022' '19/02/2022'

 '2022-09-14' '2022-05-28' 'Feb 10 2023' '2022-01-13' nan '2022-11-27'

 'Dec 05 2023' '09/04/2023' nan nan '2022-11-25' '2022-11-03' '2023-10-10'

 '2023-12-02' '2023-12-04' nan nan nan nan '27/07/2022' 'Sep 11 2022'

 '2023-10-17' '2022-10-10' '2022-06-21' '2023-02-14' '2022-08-26'

 '2023-10-13' '2023-10-26' '2022-08-12' '2023-01-22' '20/12/2023'

 'Jun 26 2023' '07/06/2022' '08/03/2023' '2023-03-29' '2023-04-23'

 '2022-01-19' '2022-08-07' '2023-09-16' '26/06/2022' '2022-08-07' nan nan

 '2022-04-24' '2022-09-11' 'Oct 01 2023' 'Jan 02 2022' '26/07/2022'

 'Feb 14 2022' '2023-02-14' '2022-07-02' '2023-08-02' '2023-03-04'

 '27/07/2023' '2023-04-09' '2022-11-17' '21/09/2023' '2022-12-14'

 '2023-11-25' '2023-12-28' '2023-03-06' '08/05/2023' '2022-07-06'

 '18/08/2023' '2023-05-06' nan '2022-07-14' '2023-07-29' 'Dec 10 2022'

 '2022-05-16' '2022-05-05' '2023-02-15' '2022-08-22' '2022-03-16'

 'Nov 08 2022' '2023-04-22' '2022-08-21' '2023-11-29' '2023-07-24'

 '10/01/2023' '2023-11-14' '2022-11-13' 'Apr 12 2022' 'Jan 27 2022'

 '2023-11-16' 'Dec 02 2023' '24/06/2023' '2022-03-17' '2022-08-03'

 '30/01/2022' nan '2022-06-29' 'Feb 22 2023' '2022-02-17' 'Dec 20 2023'

 '2022-11-29' '12/07/2022' '2023-01-12' '2023-07-31' '2022-08-17'

 'Feb 04 2022' '2022-02-07' nan 'Mar 23 2022' '2023-04-09' '2022-10-08'

 '2023-07-22' '2022-02-14' '2023-10-18' '2023-05-25' 'Nov 24 2022' nan

 '15/12/2023' '2022-08-09' nan '2022-10-15' '2022-06-18' nan '2022-04-21'

 'Jan 02 2022' '2022-07-31' '2022-03-23' '2022-10-30' '2023-09-22'

 '29/04/2022' 'Jan 01 2022' '2022-03-23' '06/01/2023' 'Jul 20 2022'

 '2022-12-24' 'Jan 22 2022' nan '2022-10-27' '2022-11-11' '2023-02-07'

 '2023-07-24' '2022-12-08' '2023-09-07' '2022-08-09' '2022-08-17'

 'Oct 01 2023' nan '2023-03-11' '11/07/2022' '2022-03-25' 'May 26 2023'

 '2023-04-25' '2023-12-05' '2022-07-30' '2022-08-22' '2023-08-09'

 '18/08/2023' '2023-12-10' '2023-01-23' '20/07/2022' '2023-07-22'

 'Feb 05 2022' '2022-10-20'] to numeric

  Step  5 | score=0.2019 | 

action={"operation":"fix_format","column":"signup_date"}

           -> Fixed 90 dates in 'signup_date' to YYYY-MM-DD format.

[STEP] step=5 action={"operation":"fix_format","column":"signup_date"} reward=0.13 done=false error=null

  Step  6 | score=0.3320 | action={"operation":"fix_format","column":"country"}

           -> Fixed 112 country values to correct capitalisation.

[STEP] step=6 action={"operation":"fix_format","column":"country"} reward=0.17 done=false error=null

  Step  7 | score=0.5070 | action={"operation":"drop_duplicates"}

           -> Dropped 20 duplicate rows.

[STEP] step=7 action={"operation":"drop_duplicates"} reward=0.20 done=false error=null

  Step  8 | score=0.7100 | 

action={"operation":"drop_outliers","column":"purchase_amount"}

           -> Removed 5 outlier rows from 'purchase_amount' using IQR method.

[STEP] step=8 action={"operation":"drop_outliers","column":"purchase_amount"} reward=0.20 done=false error=null

  Step  9 | score=0.9100 | action={"operation":"fill_missing","column":"signup_d

ate","params":{"strategy":"median"}}

           -> Operation failed: Cannot convert [nan '2022-12-15' '2023-12-20' 

nan '2023-04-21' '2023-10-22' nan

 '2023-06-11' '2022-07-27' '2023-12-05' '2023-04-01' '2023-07-25'

 '2022-12-03' '2023-09-25' '2022-02-24' '2022-03-25' '2023-01-06'

 '2023-06-19' '2023-08-14' '2022-11-18' '2023-04-20' '2023-02-08'

 '2023-12-03' '2023-04-23' '2022-11-01' '2023-12-09' '2022-03-20' nan

 '2022-04-23' '2022-07-30' '2023-08-23' '2023-06-20' '2023-12-10'

 '2023-07-02' '2023-04-11' '2022-09-10' '2022-01-04' '2022-04-01'

 '2022-01-30' '2023-01-06' '2023-07-22' '2023-12-05' '2022-12-24'

 '2023-10-01' '2023-12-21' '2023-09-20' '2022-12-06' '2022-08-26'

 '2023-12-15' '2022-06-26' '2022-10-28' '2022-02-24' '2023-08-03'

 '2023-04-20' nan '2022-06-12' '2023-02-10' nan '2023-08-09' '2022-07-14'

 '2023-11-07' '2022-11-21' '2023-08-24' '2022-06-24' '2022-01-27'

 '2022-02-10' '2022-09-30' '2023-11-27' '2022-02-05' '2022-09-27'

 '2022-03-21' '2023-11-12' '2023-05-08' '2023-07-11' '2023-06-05'

 '2023-04-25' '2022-01-06' '2023-09-24' '2023-06-25' '2023-06-24'

 '2022-10-15' '2023-08-08' '2022-10-06' '2022-02-05' '2023-10-25'

 '2022-06-21' '2022-03-16' '2023-03-30' '2022-06-20' '2023-09-19' nan

 '2022-01-04' '2023-11-26' '2023-01-11' '2022-07-11' '2023-05-10'

 '2023-01-23' '2022-01-22' nan '2022-10-20' '2023-05-26' '2023-10-16'

 '2023-03-22' nan '2022-07-05' '2022-06-23' '2022-10-30' '2023-09-15'

 '2023-01-18' '2022-09-12' '2023-07-24' nan '2023-10-21' '2022-08-07'

 '2023-06-03' '2023-03-07' nan '2022-10-17' nan '2022-07-20' '2023-02-06'

 '2023-10-10' '2023-09-25' nan '2023-05-11' '2022-03-03' '2023-05-08'

 '2022-09-07' '2022-11-25' '2023-06-08' '2022-11-07' '2023-08-13'

 '2023-01-25' '2023-04-11' '2022-08-05' '2023-07-20' '2022-10-25'

 '2022-04-10' '2022-03-29' '2023-02-24' '2022-05-17' '2023-12-30'

 '2023-09-17' '2023-05-27' '2023-06-21' '2023-03-11' '2022-02-14' nan

 '2022-12-28' '2022-06-10' '2022-12-29' '2022-09-09' '2022-04-09'

 '2022-03-17' '2022-09-24' '2022-03-02' '2022-02-19' '2022-09-14'

 '2022-05-28' '2023-02-10' '2022-01-13' nan '2022-11-27' '2023-12-05'

 '2023-04-09' nan nan '2022-11-25' '2022-11-03' '2023-10-10' '2023-12-02'

 '2023-12-04' nan nan nan nan '2022-07-27' '2022-09-11' '2023-10-17'

 '2022-10-10' '2022-06-21' '2023-02-14' '2022-08-26' '2023-10-13'

 '2023-10-26' '2022-08-12' '2023-01-22' '2023-12-20' '2023-06-26'

 '2022-06-07' '2023-03-08' '2023-03-29' '2023-04-23' '2022-01-19'

 '2022-08-07' '2023-09-16' '2022-06-26' '2022-08-07' nan nan '2022-04-24'

 '2022-09-11' '2023-10-01' '2022-01-02' '2022-07-26' '2022-02-14'

 '2023-02-14' '2022-07-02' '2023-08-02' '2023-03-04' '2023-07-27'

 '2023-04-09' '2022-11-17' '2023-09-21' '2022-12-14' '2023-11-25'

 '2023-12-28' '2023-03-06' '2023-05-08' '2022-07-06' '2023-08-18'

 '2023-05-06' nan '2022-07-14' '2023-07-29' '2022-12-10' '2022-05-16'

 '2022-05-05' '2023-02-15' '2022-08-22' '2022-03-16' '2022-11-08'

 '2023-04-22' '2022-08-21' '2023-11-29' '2023-07-24' '2023-01-10'

 '2023-11-14' '2022-11-13' '2022-04-12' '2022-01-27' '2023-11-16'

 '2023-12-02' '2023-06-24' '2022-03-17' '2022-08-03' '2022-01-30' nan

 '2022-06-29' '2023-02-22' '2022-02-17' '2023-12-20' '2022-11-29'

 '2022-07-12' '2023-01-12' '2023-07-31' '2022-08-17' '2022-02-04'

 '2022-02-07' nan '2022-03-23' '2023-04-09' '2022-10-08' '2023-07-22'

 '2022-02-14' '2023-10-18' '2023-05-25' '2022-11-24' nan '2023-12-15'

 '2022-08-09' nan '2022-10-15' '2022-06-18' nan '2022-04-21' '2022-01-02'

 '2022-07-31' '2022-03-23' '2022-10-30' '2023-09-22' '2022-04-29'

 '2022-01-01' '2022-03-23' '2023-01-06' '2022-07-20' '2022-12-24'

 '2022-01-22' nan '2022-10-27' '2022-11-11' '2023-02-07' '2023-07-24'

 '2022-12-08' '2023-09-07'] to numeric

[STEP] step=9 action={"operation":"fill_missing","column":"signup_date","params":{"strategy":"median"}} reward=0.01 done=false error=null

  Step 10 | score=0.9100 | action={"operation":"fill_missing","column":"signup_d

ate","params":{"strategy":"mode"}}

           -> Filled 30 missing values in 'signup_date' using mode.



[STEP] step=10 action={"operation":"fill_missing","column":"signup_date","params":{"strategy":"mode"}} reward=0.08 done=true error=null

[END] task=data-cleaning-task3 score=0.9900 steps=10

  Task 3 final score: 0.9900  (steps used: 10)



============================================================

  BASELINE RESULTS

============================================================

  task1: 0.9900

  task2: 0.9900

  task3: 0.9900

  average: 0.9900

============================================================



Scores written to baseline_scores.json