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README.md: add syntax hint

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Jörg Thalheim 2016-05-31 11:39:25 +00:00
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@ -6,7 +6,7 @@ a new fast and accurate unsupervised Time Series cluster algorithm.
## Usage ## Usage
``` ```python
from kshape import kshape, zscore from kshape import kshape, zscore
time_series = [[1,2,3,4], [0,1,2,3], [0,1,2,3], [1,2,2,3]] time_series = [[1,2,3,4], [0,1,2,3], [0,1,2,3], [1,2,2,3]]
@ -28,7 +28,7 @@ and the corresponding centroid.
- In the following a tab seperated file is assumed, where each column is a different observation; - In the following a tab seperated file is assumed, where each column is a different observation;
gapps in columns happen, when only a certain value at this point in time was obtained. gapps in columns happen, when only a certain value at this point in time was obtained.
``` ```python
import pandas as pd import pandas as pd
# assuming the time series are stored in a tab seperated file, where `time` is # assuming the time series are stored in a tab seperated file, where `time` is
# the name of the column containing the timestamp # the name of the column containing the timestamp
@ -43,7 +43,7 @@ df.fillna(method="bfill", inplace=True)
- kshape also expect no time series with a constant observation value or 'n/a' - kshape also expect no time series with a constant observation value or 'n/a'
``` ```python
time_series = [] time_series = []
for f in df.columns: for f in df.columns:
if not df[f].isnull().any() and df[f].var() != 0: if not df[f].isnull().any() and df[f].var() != 0:
@ -52,7 +52,7 @@ for f in df.columns:
## Relevant Articles ## Relevant Articles
``` ```plain
Paparrizos J and Gravano L (2015). Paparrizos J and Gravano L (2015).
k-Shape: Efficient and Accurate Clustering of Time Series. k-Shape: Efficient and Accurate Clustering of Time Series.
In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, series SIGMOD '15, In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, series SIGMOD '15,