Kernel: Python 3 (Anaconda)
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<matplotlib.axes._subplots.AxesSubplot at 0x7f4384188e80>
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<matplotlib.axes._subplots.AxesSubplot at 0x7f438341b8d0>
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count 1.009790e+05
mean NaN
std NaN
min -inf
25% -1.200000e+00
50% 0.000000e+00
75% 1.000000e+00
max inf
dtype: float64
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Time
2016-02-19 13:26:00 NaN
2016-02-19 13:27:00 NaN
2016-02-19 13:27:00 NaN
2016-02-19 13:31:00 NaN
2016-02-19 13:36:00 -1.0
dtype: float64
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<matplotlib.axes._subplots.AxesSubplot at 0x7f4383715d30>
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Time
2016-02-19 13:26:00 NaN
2016-02-19 13:27:00 NaN
2016-02-19 13:27:00 NaN
2016-02-19 13:31:00 NaN
2016-02-19 13:36:00 -332.0
dtype: float64
made Infiltration csv (perhaps for detailed reference later)
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ppm/min | |
---|---|
Time | |
2016-02-19 13:26:00 | NaN |
2016-02-19 13:27:00 | NaN |
2016-02-19 13:27:00 | NaN |
2016-02-19 13:31:00 | NaN |
2016-02-19 13:36:00 | -332.0 |
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ppm/min | |
---|---|
count | 4.885000e+04 |
mean | -inf |
std | NaN |
min | -inf |
25% | -1.046850e+03 |
50% | -5.160000e+02 |
75% | -2.460000e+02 |
max | -2.306667e+01 |
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ppm/min | |
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count | 48848.000000 |
mean | -1141.663669 |
std | 3186.375410 |
min | -206960.600000 |
25% | -1046.400000 |
50% | -516.000000 |
75% | -246.000000 |
max | -23.066667 |
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array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f4382e699e8>]], dtype=object)
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array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f4382df5160>]], dtype=object)
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array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f437f04c358>]], dtype=object)
Question for Soto: how to make bins small enough to fit each value, or at least equal to the average difference
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array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f43834fc828>]], dtype=object)
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array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f437de3b2b0>]], dtype=object)
This needs some work
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/ext/anaconda3/lib/python3.5/site-packages/matplotlib/axes/_axes.py:6277: RuntimeWarning: invalid value encountered in add
patch = _barfunc(bins[:-1]+boffset, height, width,
/ext/anaconda3/lib/python3.5/site-packages/matplotlib/axes/_axes.py:2105: RuntimeWarning: invalid value encountered in double_scalars
left = [left[i] - width[i] / 2. for i in xrange(len(left))]
array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f437d8a0b70>]], dtype=object)
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---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-23-a2f1855ae631> in <module>()
----> 1 In.kdeplot()
/ext/anaconda3/lib/python3.5/site-packages/pandas/core/generic.py in __getattr__(self, name)
3079 if name in self._info_axis:
3080 return self[name]
-> 3081 return object.__getattribute__(self, name)
3082
3083 def __setattr__(self, name, value):
AttributeError: 'DataFrame' object has no attribute 'kdeplot'
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