# Checking for decreasing values in a timeseries

Example of algorithm that indicates decreasing values in time series data. This algorithm is applied on Running Hours time series. It is a specific type of time series that is counting the number of running hours in a pump. Given that we expect the number of running hours to either stay the same (if the pump is not running) or increase with time (if the pump is running), the decrease in running hours value indicates bad data quality.

The output of the algorithm is an indicator time series with value 1 where there is a decrease in time series value, and 0 otherwise. The indicator will be set to 1 until the data gets “back to normal” (that is, until time series reaches the value it had before the value drop).

The algorithm is applied on the same data twice:

1. Using default threshold; indicator will be set to 1 if data drop is higher than 0

2. Using a threshold of 4.1; indicator will be set to 1 if data drop is higher than 4.1

```import os

import matplotlib.pyplot as plt
import pandas as pd

from indsl.data_quality.value_decrease_indication import value_decrease_check

# import generated data
base_path = "" if __name__ == "__main__" else os.path.dirname(__file__)
data = data.squeeze()
data.index = pd.to_datetime(data.index)

# apply the function for checking decrease in time series values - use default threshold (0.0)
indicator_default_threshold = value_decrease_check(data)

# apply the function for checking decrease in time series values - change the threshold (4.1)
indicator_new_threshold = value_decrease_check(data, 4.1)

# plot the results
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(9, 7))
ax1.plot(data, "-")
ax2.plot(indicator_default_threshold, "-")
ax3.plot(indicator_new_threshold, "-")
ax1.set_title("Time series values")
ax2.set_title("Indicator with default threshold 0.0")
ax3.set_title("Indicator with threshold 4.1")
fig.suptitle("Indicator for decrease in time series values", fontsize=16)
fig.tight_layout()

plt.show()
```

Total running time of the script: ( 0 minutes 34.568 seconds)

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