Sometimes its useful to be able to read an existing .res.csv
results file from an earlier Source run
Normally when working with Veneer, you retreive time series results directly from the running copy of Source. This data is transferred as JSON encoded text, but you see a Pandas Dataframe as the result of v.retrieve_multiple_timeseries
.
This notebook demonstrates a provided function for reading .res.csv
files into a Python session. The result is TWO dataframes - one dataframe containing the time series data (one column per timeseries, indexed by date/time) and one dataframe containing the metadata on the time series.
In [2]:
import veneer
from veneer import read_rescsv
In [3]:
metadata, data = read_rescsv('example.res.csv')
In [4]:
metadata
Out[4]:
Custom
ElementName
ElementType
Field
Name
RunName
ScenarioInputSetName
ScenarioName
Site
Structure
Units
WaterFeatureType
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11>node #10>Downstream Flow
7>node #1>Downstream Flow Volume
9>node #1>Upstream Flow
Date
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2>node #0>Downstream Flow Volume
4>node #0>Upstream Flow
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data
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1900-01-19
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1900-01-20
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1900-01-21
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1900-01-22
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1900-01-23
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1900-01-24
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1900-01-25
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1900-01-26
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1900-01-27
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1900-01-28
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1900-01-29
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1900-01-30
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NaN
...
...
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...
...
...
...
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1900-12-02
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1900-12-03
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1900-12-04
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1900-12-05
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1900-12-06
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0.047130
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1900-12-07
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0.402958
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0.044773
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1900-12-08
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1900-12-09
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0.363669
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0.040408
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1900-12-10
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0.038387
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1900-12-11
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0.328212
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1900-12-12
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0.311801
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0.034645
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NaN
1900-12-13
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0.296211
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0.032912
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1900-12-14
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0.281400
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1900-12-15
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0.267330
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0.029703
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1900-12-16
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1900-12-17
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1900-12-18
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0.025467
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1900-12-19
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1900-12-20
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1900-12-21
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1900-12-22
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1900-12-23
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1900-12-24
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1900-12-25
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1900-12-26
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1900-12-27
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1900-12-28
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0.137232
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1900-12-29
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1900-12-30
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1900-12-31
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0.117659
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0.104586
0.104586
NaN
365 rows × 207 columns
In [ ]:
Content source: ConnectedSystems/veneer-py
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