# korexo_profile
Read KorEXO sonde profile CSV files.
Full package documentation is on [Read the Docs](https://korexo-profile.readthedocs.io/en/latest/).
## Install
```bash
$ pip install korexo_profile
```
## Usage
KorEXO file straight to a table:
```python
>>> import korexo_profile
>>> data = korexo_profile.read("../tests/example1_full.csv")
>>> df = korexo_profile.convert_datasets_to_df(data["datasets"])
```
Or, for the full set of information:
```python
>>> import korexo_profile
>>> data = korexo_profile.read("../tests/example2.csv")
>>> data.keys()
dict_keys(['metadata', 'datasets', 'dataframe'])
>>> df = data["dataframe"]
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 9 entries, 0 to 8
Data columns (total 22 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 Date (MM/DD/YYYY) 9 non-null object
1 Time (HH:mm:ss) 9 non-null object
2 Time (Fract. Sec) 9 non-null int64
3 Site Name 9 non-null object
4 Cond µS/cm 9 non-null int64
5 Depth m 9 non-null float64
6 nLF Cond µS/cm 9 non-null float64
7 ODO % sat 9 non-null float64
8 ODO % local 9 non-null float64
9 ODO mg/L 9 non-null float64
10 ORP mV 9 non-null float64
11 Pressure psi a 9 non-null float64
12 Sal psu 9 non-null int64
13 SpCond µS/cm 9 non-null float64
14 TDS mg/L 9 non-null int64
15 pH 9 non-null float64
16 pH mV 9 non-null float64
17 Temp °C 9 non-null float64
18 Vertical Position m 9 non-null float64
19 Battery V 9 non-null float64
20 Cable Pwr V 9 non-null float64
21 DTW 1 non-null float64
dtypes: float64(15), int64(4), object(3)
memory usage: 1.7+ KB
```
Or each dataset at a time:
```
>>> data["datasets"][0]
{'name': 'Date',
'column': 'Date (MM/DD/YYYY)',
'sensor': '',
'mean': <NA>,
'stdev': <NA>,
'data': [datetime.date(2020, 10, 16),
datetime.date(2020, 10, 16),
datetime.date(2020, 10, 16),
datetime.date(2020, 10, 16),
datetime.date(2020, 10, 16),
datetime.date(2020, 10, 16),
datetime.date(2020, 10, 16),
datetime.date(2020, 10, 16),
datetime.date(2020, 10, 16)],
'median': datetime.date(2020, 10, 16)}
>>> data["datasets"][1]
{'name': 'Time',
'column': 'Time (HH:mm:ss)',
'sensor': '',
'mean': <NA>,
'stdev': <NA>,
'data': array(['15:49:33', '15:49:34', '15:49:35', '15:49:36', '15:49:37',
'15:49:38', '15:49:39', '15:49:40', '15:49:41'], dtype=object),
'median': '15:49:33'}
>>> data["datasets"][9]
{'name': 'ODO mg/L',
'column': 'ODO mg/L',
'sensor': '19D101830',
'mean': 7.66,
'stdev': 0.97,
'data': array([9.5 , 9.5 , 9.49, 9.49, 9.5 , 9.49, 9.49, 9.5 , 9.49]),
'median': 9.49}
```
And the metadata:
```python
>>> data["metadata"]
{'created_file': datetime.datetime(2022, 4, 7, 16, 45, 10, 874033),
'modified_file': datetime.datetime(2022, 4, 7, 16, 45, 10, 875029),
'created_info': '10/16/2020 6:21:53 AM,,,,,,,,,,,,,,,,,,,,',
'header_line_no': 9,
'params': ['Cond µS/cm',
'Depth m',
'nLF Cond µS/cm',
'ODO % sat',
'ODO % local',
'ODO mg/L',
'ORP mV',
'Pressure psi a',
'Sal psu',
'SpCond µS/cm',
'TDS mg/L',
'pH',
'pH mV',
'Temp °C',
'Vertical Position m',
'Battery V',
'Cable Pwr V',
'DTW'],
'sensors': ['19A103955',
'19B104242',
'19A103955',
'19D101830',
'19D101830',
'19D101830',
'19B105042',
'19B104242',
'19A103955',
'19A103955',
'19A103955',
'19B105042',
'19B105042',
'19A103955',
'19B104242',
'19C000969',
'19C000969',
''],
'means': [1172.5,
0.605,
1277.2,
85.5,
85.6,
7.66,
47.1,
0.859,
0.64,
1268.1,
824,
<NA>,
-126,
20.679,
0.812,
3.13,
11.4,
nan],
'stdevs': [566.7,
0.791,
617.1,
9.2,
9.2,
0.97,
1.1,
1.123,
0.31,
612.7,
398,
0.1,
5.7,
0.8,
0.972,
0,
0,
nan]}
```
Full package documentation is on [Read the Docs](https://korexo-profile.readthedocs.io/en/latest/).
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"description": "# korexo_profile\n\nRead KorEXO sonde profile CSV files.\n\nFull package documentation is on [Read the Docs](https://korexo-profile.readthedocs.io/en/latest/).\n\n## Install\n\n```bash\n$ pip install korexo_profile\n```\n## Usage\n\nKorEXO file straight to a table:\n\n```python\n>>> import korexo_profile\n>>> data = korexo_profile.read(\"../tests/example1_full.csv\")\n>>> df = korexo_profile.convert_datasets_to_df(data[\"datasets\"])\n```\n\nOr, for the full set of information:\n\n```python\n>>> import korexo_profile\n>>> data = korexo_profile.read(\"../tests/example2.csv\")\n>>> data.keys()\ndict_keys(['metadata', 'datasets', 'dataframe'])\n>>> df = data[\"dataframe\"]\n>>> df.info()\n<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 9 entries, 0 to 8\nData columns (total 22 columns):\n # Column Non-Null Count Dtype\n--- ------ -------------- -----\n 0 Date (MM/DD/YYYY) 9 non-null object\n 1 Time (HH:mm:ss) 9 non-null object\n 2 Time (Fract. Sec) 9 non-null int64\n 3 Site Name 9 non-null object\n 4 Cond \u00b5S/cm 9 non-null int64\n 5 Depth m 9 non-null float64\n 6 nLF Cond \u00b5S/cm 9 non-null float64\n 7 ODO % sat 9 non-null float64\n 8 ODO % local 9 non-null float64\n 9 ODO mg/L 9 non-null float64\n 10 ORP mV 9 non-null float64\n 11 Pressure psi a 9 non-null float64\n 12 Sal psu 9 non-null int64\n 13 SpCond \u00b5S/cm 9 non-null float64\n 14 TDS mg/L 9 non-null int64\n 15 pH 9 non-null float64\n 16 pH mV 9 non-null float64\n 17 Temp \u00b0C 9 non-null float64\n 18 Vertical Position m 9 non-null float64\n 19 Battery V 9 non-null float64\n 20 Cable Pwr V 9 non-null float64\n 21 DTW 1 non-null float64\ndtypes: float64(15), int64(4), object(3)\nmemory usage: 1.7+ KB\n```\n\nOr each dataset at a time:\n\n```\n>>> data[\"datasets\"][0]\n{'name': 'Date',\n 'column': 'Date (MM/DD/YYYY)',\n 'sensor': '',\n 'mean': <NA>,\n 'stdev': <NA>,\n 'data': [datetime.date(2020, 10, 16),\n datetime.date(2020, 10, 16),\n datetime.date(2020, 10, 16),\n datetime.date(2020, 10, 16),\n datetime.date(2020, 10, 16),\n datetime.date(2020, 10, 16),\n datetime.date(2020, 10, 16),\n datetime.date(2020, 10, 16),\n datetime.date(2020, 10, 16)],\n 'median': datetime.date(2020, 10, 16)}\n>>> data[\"datasets\"][1]\n{'name': 'Time',\n 'column': 'Time (HH:mm:ss)',\n 'sensor': '',\n 'mean': <NA>,\n 'stdev': <NA>,\n 'data': array(['15:49:33', '15:49:34', '15:49:35', '15:49:36', '15:49:37',\n '15:49:38', '15:49:39', '15:49:40', '15:49:41'], dtype=object),\n 'median': '15:49:33'}\n>>> data[\"datasets\"][9]\n{'name': 'ODO mg/L',\n 'column': 'ODO mg/L',\n 'sensor': '19D101830',\n 'mean': 7.66,\n 'stdev': 0.97,\n 'data': array([9.5 , 9.5 , 9.49, 9.49, 9.5 , 9.49, 9.49, 9.5 , 9.49]),\n 'median': 9.49}\n```\n\nAnd the metadata:\n\n```python\n>>> data[\"metadata\"]\n{'created_file': datetime.datetime(2022, 4, 7, 16, 45, 10, 874033),\n 'modified_file': datetime.datetime(2022, 4, 7, 16, 45, 10, 875029),\n 'created_info': '10/16/2020 6:21:53 AM,,,,,,,,,,,,,,,,,,,,',\n 'header_line_no': 9,\n 'params': ['Cond \u00b5S/cm',\n 'Depth m',\n 'nLF Cond \u00b5S/cm',\n 'ODO % sat',\n 'ODO % local',\n 'ODO mg/L',\n 'ORP mV',\n 'Pressure psi a',\n 'Sal psu',\n 'SpCond \u00b5S/cm',\n 'TDS mg/L',\n 'pH',\n 'pH mV',\n 'Temp \u00b0C',\n 'Vertical Position m',\n 'Battery V',\n 'Cable Pwr V',\n 'DTW'],\n 'sensors': ['19A103955',\n '19B104242',\n '19A103955',\n '19D101830',\n '19D101830',\n '19D101830',\n '19B105042',\n '19B104242',\n '19A103955',\n '19A103955',\n '19A103955',\n '19B105042',\n '19B105042',\n '19A103955',\n '19B104242',\n '19C000969',\n '19C000969',\n ''],\n 'means': [1172.5,\n 0.605,\n 1277.2,\n 85.5,\n 85.6,\n 7.66,\n 47.1,\n 0.859,\n 0.64,\n 1268.1,\n 824,\n <NA>,\n -126,\n 20.679,\n 0.812,\n 3.13,\n 11.4,\n nan],\n 'stdevs': [566.7,\n 0.791,\n 617.1,\n 9.2,\n 9.2,\n 0.97,\n 1.1,\n 1.123,\n 0.31,\n 612.7,\n 398,\n 0.1,\n 5.7,\n 0.8,\n 0.972,\n 0,\n 0,\n nan]}\n```\n\nFull package documentation is on [Read the Docs](https://korexo-profile.readthedocs.io/en/latest/).\n",
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