Interactive labeling/annotating of time series data
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I have a data set of time series data. I'm looking for an annotation (or labeling) tool to visualize it and to be able to interactively add labels on it, in order to get annotated data that I can use for supervised ML.
E.g. the input data is a csv-file and the output is another csv-file of the format timestamp,label.
Therefore I need something like this:
- to visualize data
- to select a specific area
- output the labels with timestamps
As an example:
Building such a tool in python will not take too long, however I was just wondering how other people solve this problem and maybe there are already nice OS tools for doing this. Thank you!
machine-learning python data labels
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bumped to the homepage by Community♦ 11 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I have a data set of time series data. I'm looking for an annotation (or labeling) tool to visualize it and to be able to interactively add labels on it, in order to get annotated data that I can use for supervised ML.
E.g. the input data is a csv-file and the output is another csv-file of the format timestamp,label.
Therefore I need something like this:
- to visualize data
- to select a specific area
- output the labels with timestamps
As an example:
Building such a tool in python will not take too long, however I was just wondering how other people solve this problem and maybe there are already nice OS tools for doing this. Thank you!
machine-learning python data labels
$endgroup$
bumped to the homepage by Community♦ 11 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
$begingroup$
If you're plotting in python, chances are your best bet is to annotate in python, not in the OS.
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– Adrian Keister
Sep 13 '18 at 15:56
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@AdrianKeister When I wrote OS, I meant an open source project.
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– mibrl12
Sep 14 '18 at 11:31
add a comment |
$begingroup$
I have a data set of time series data. I'm looking for an annotation (or labeling) tool to visualize it and to be able to interactively add labels on it, in order to get annotated data that I can use for supervised ML.
E.g. the input data is a csv-file and the output is another csv-file of the format timestamp,label.
Therefore I need something like this:
- to visualize data
- to select a specific area
- output the labels with timestamps
As an example:
Building such a tool in python will not take too long, however I was just wondering how other people solve this problem and maybe there are already nice OS tools for doing this. Thank you!
machine-learning python data labels
$endgroup$
I have a data set of time series data. I'm looking for an annotation (or labeling) tool to visualize it and to be able to interactively add labels on it, in order to get annotated data that I can use for supervised ML.
E.g. the input data is a csv-file and the output is another csv-file of the format timestamp,label.
Therefore I need something like this:
- to visualize data
- to select a specific area
- output the labels with timestamps
As an example:
Building such a tool in python will not take too long, however I was just wondering how other people solve this problem and maybe there are already nice OS tools for doing this. Thank you!
machine-learning python data labels
machine-learning python data labels
asked Sep 11 '18 at 6:19
mibrl12mibrl12
1261
1261
bumped to the homepage by Community♦ 11 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 11 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
$begingroup$
If you're plotting in python, chances are your best bet is to annotate in python, not in the OS.
$endgroup$
– Adrian Keister
Sep 13 '18 at 15:56
$begingroup$
@AdrianKeister When I wrote OS, I meant an open source project.
$endgroup$
– mibrl12
Sep 14 '18 at 11:31
add a comment |
$begingroup$
If you're plotting in python, chances are your best bet is to annotate in python, not in the OS.
$endgroup$
– Adrian Keister
Sep 13 '18 at 15:56
$begingroup$
@AdrianKeister When I wrote OS, I meant an open source project.
$endgroup$
– mibrl12
Sep 14 '18 at 11:31
$begingroup$
If you're plotting in python, chances are your best bet is to annotate in python, not in the OS.
$endgroup$
– Adrian Keister
Sep 13 '18 at 15:56
$begingroup$
If you're plotting in python, chances are your best bet is to annotate in python, not in the OS.
$endgroup$
– Adrian Keister
Sep 13 '18 at 15:56
$begingroup$
@AdrianKeister When I wrote OS, I meant an open source project.
$endgroup$
– mibrl12
Sep 14 '18 at 11:31
$begingroup$
@AdrianKeister When I wrote OS, I meant an open source project.
$endgroup$
– mibrl12
Sep 14 '18 at 11:31
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
I'm using axvspan() function from matplotlib.pyplot.
Main disadvantage is a difficult configuration of text labels.
import matplotlib.pyplot as plt
import numpy as np
t = np.arange(0,3.14,0.01)
s = np.sin(t)
plt.axvspan(t[12], t[100], facecolor='blue', alpha=0.2)
plt.plot(t,s,color='red')
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add a comment |
$begingroup$
Nova can do it interactively. https://github.com/hcmlab/nova
It's much more powerful than just labeling time-series data, but you can just do labeling with it. Also, I suggest you set the sample rate frequency to 1Hz. Best of Luck.
$endgroup$
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
I'm using axvspan() function from matplotlib.pyplot.
Main disadvantage is a difficult configuration of text labels.
import matplotlib.pyplot as plt
import numpy as np
t = np.arange(0,3.14,0.01)
s = np.sin(t)
plt.axvspan(t[12], t[100], facecolor='blue', alpha=0.2)
plt.plot(t,s,color='red')
$endgroup$
add a comment |
$begingroup$
I'm using axvspan() function from matplotlib.pyplot.
Main disadvantage is a difficult configuration of text labels.
import matplotlib.pyplot as plt
import numpy as np
t = np.arange(0,3.14,0.01)
s = np.sin(t)
plt.axvspan(t[12], t[100], facecolor='blue', alpha=0.2)
plt.plot(t,s,color='red')
$endgroup$
add a comment |
$begingroup$
I'm using axvspan() function from matplotlib.pyplot.
Main disadvantage is a difficult configuration of text labels.
import matplotlib.pyplot as plt
import numpy as np
t = np.arange(0,3.14,0.01)
s = np.sin(t)
plt.axvspan(t[12], t[100], facecolor='blue', alpha=0.2)
plt.plot(t,s,color='red')
$endgroup$
I'm using axvspan() function from matplotlib.pyplot.
Main disadvantage is a difficult configuration of text labels.
import matplotlib.pyplot as plt
import numpy as np
t = np.arange(0,3.14,0.01)
s = np.sin(t)
plt.axvspan(t[12], t[100], facecolor='blue', alpha=0.2)
plt.plot(t,s,color='red')
answered Dec 18 '18 at 20:57
RolanRolan
1
1
add a comment |
add a comment |
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Nova can do it interactively. https://github.com/hcmlab/nova
It's much more powerful than just labeling time-series data, but you can just do labeling with it. Also, I suggest you set the sample rate frequency to 1Hz. Best of Luck.
$endgroup$
add a comment |
$begingroup$
Nova can do it interactively. https://github.com/hcmlab/nova
It's much more powerful than just labeling time-series data, but you can just do labeling with it. Also, I suggest you set the sample rate frequency to 1Hz. Best of Luck.
$endgroup$
add a comment |
$begingroup$
Nova can do it interactively. https://github.com/hcmlab/nova
It's much more powerful than just labeling time-series data, but you can just do labeling with it. Also, I suggest you set the sample rate frequency to 1Hz. Best of Luck.
$endgroup$
Nova can do it interactively. https://github.com/hcmlab/nova
It's much more powerful than just labeling time-series data, but you can just do labeling with it. Also, I suggest you set the sample rate frequency to 1Hz. Best of Luck.
answered Jan 11 at 6:33
drerDdrerD
1
1
add a comment |
add a comment |
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$begingroup$
If you're plotting in python, chances are your best bet is to annotate in python, not in the OS.
$endgroup$
– Adrian Keister
Sep 13 '18 at 15:56
$begingroup$
@AdrianKeister When I wrote OS, I meant an open source project.
$endgroup$
– mibrl12
Sep 14 '18 at 11:31