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Ryan Randles Jones
createAndParseSACCT
Commits
9bfd57c5
Commit
9bfd57c5
authored
5 years ago
by
Ryan Randles Jones
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parent
4d36cdff
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1 merge request
!1
Kmeans clustering
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importSACCTinfo.ipynb
+6
-85
6 additions, 85 deletions
importSACCTinfo.ipynb
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6
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85
View file @
9bfd57c5
...
@@ -3,12 +3,7 @@
...
@@ -3,12 +3,7 @@
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": null,
"execution_count": null,
"metadata": {
"metadata": {},
"ExecuteTime": {
"end_time": "2020-03-16T20:57:10.405006Z",
"start_time": "2020-03-16T20:56:55.837670Z"
}
},
"outputs": [],
"outputs": [],
"source": [
"source": [
"import numpy as np\n",
"import numpy as np\n",
...
@@ -19,12 +14,7 @@
...
@@ -19,12 +14,7 @@
{
{
"cell_type": "code",
"cell_type": "code",
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"end_time": "2020-03-16T20:57:11.865980Z",
"start_time": "2020-03-16T20:57:10.414986Z"
}
},
"outputs": [],
"outputs": [],
"source": [
"source": [
"df = pd.read_csv('userusage.txt',delimiter='|')"
"df = pd.read_csv('userusage.txt',delimiter='|')"
...
@@ -33,12 +23,7 @@
...
@@ -33,12 +23,7 @@
{
{
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"end_time": "2020-03-16T20:57:11.932878Z",
"start_time": "2020-03-16T20:57:11.905219Z"
}
},
"outputs": [],
"outputs": [],
"source": [
"source": [
"df.head()"
"df.head()"
...
@@ -47,12 +32,7 @@
...
@@ -47,12 +32,7 @@
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"start_time": "2020-03-16T20:57:11.967976Z"
}
},
"outputs": [],
"outputs": [],
"source": [
"source": [
"df[['jid','step']] = df.JobID.str.split(\".\",expand=True) \n",
"df[['jid','step']] = df.JobID.str.split(\".\",expand=True) \n",
...
@@ -62,11 +42,7 @@
...
@@ -62,11 +42,7 @@
{
{
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}
},
"outputs": [],
"outputs": [],
"source": [
"source": [
"batchDF=df.dropna(subset=[\"MaxRSS\"])\n",
"batchDF=df.dropna(subset=[\"MaxRSS\"])\n",
...
@@ -95,64 +71,9 @@
...
@@ -95,64 +71,9 @@
}
}
],
],
"metadata": {
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"delete_cmd_prefix": "del ",
"library": "var_list.py",
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},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
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...
...
%% Cell type:code id: tags:
%% Cell type:code id: tags:
```
python
```
import numpy as np
import numpy as np
import pandas as pd
import pandas as pd
import pandas_profiling
import pandas_profiling
```
```
%% Cell type:code id: tags:
%% Cell type:code id: tags:
```
python
```
df = pd.read_csv('userusage.txt',delimiter='|')
df = pd.read_csv('userusage.txt',delimiter='|')
```
```
%% Cell type:code id: tags:
%% Cell type:code id: tags:
```
python
```
df.head()
df.head()
```
```
%% Cell type:code id: tags:
%% Cell type:code id: tags:
```
python
```
df[['jid','step']] = df.JobID.str.split(".",expand=True)
df[['jid','step']] = df.JobID.str.split(".",expand=True)
df.Partition.values
df.Partition.values
```
```
%% Cell type:code id: tags:
%% Cell type:code id: tags:
```
python
```
batchDF=df.dropna(subset=["MaxRSS"])
batchDF=df.dropna(subset=["MaxRSS"])
userDF=df.dropna(subset=["User"])
userDF=df.dropna(subset=["User"])
for jid in df.jid.unique():
for jid in df.jid.unique():
userDF['MaxRSS'][userDF['jid'] == jid]=batchDF['MaxRSS'][batchDF['jid'] == jid]
userDF['MaxRSS'][userDF['jid'] == jid]=batchDF['MaxRSS'][batchDF['jid'] == jid]
#print(userDF[userDF['jid'] == jid])
#print(userDF[userDF['jid'] == jid])
userDF.head()
userDF.head()
```
```
%% Cell type:markdown id: tags:
%% Cell type:markdown id: tags:
# add more graphs here
# add more graphs here
%% Cell type:code id: tags:
%% Cell type:code id: tags:
```
python
```
```
```
...
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