""" Function that calculates the distance between a point and centroid of a cluster, returns the distances in pandas series""" distance = [] for i in range(0,len(data)): Xa = np.array(data.loc[i]) Xb = model.cluster_centers_[model.labels_[i]-1] distance.append(np.linalg.norm(X...
# Entire "sensor_15" column is NaN therefore removing the entire column from the data set del sensor_df['sensor_15'] del sensor_df['Unnamed: 0'] # Function that calculates the percentage of missing values def calc_percent_NAs(df): nans = pd.DataFrame(df.isnull().sum().sort_values(...
This function is of type: combiner tsfresh.feature_extraction.feature_calculators.fft_coefficient(x, param) Calculates the fourier coefficients of the one-dimensional discrete Fourier Transform for real input by fast fourier transformation algorithm A k = ∑ m = 0 n − 1 a m exp { −...
Let's put all these together in a function that calculates the median of a sample. Here's a possible implementation: >>> def my_median(sample): ... n = len(sample) ... index = n // 2 ... # Sample with an odd number of observations ... if n % 2: ... return sort...
You can more clearly see what’s happening by wrapping .startswith("B") in a function that also prints out which item is being checked: Python >>> def starts_with_b(name): ... print(f"Checking {name}: {(result := name.startswith('B'))}") ... return result ... >>> ...
By default, the variance is taken from the flattened array (from all array elements), This function calculates the average of the squared deviations from the mean, i.e.,var=mean(abs(x–x.mean())**2)e. Mean isx.sum()/N, whereN=len(x)for an array x, otherwise along with the spe...
The statistics module calculates basic statistical properties (the mean, median, variance, etc.) of numeric data:>>> >>> import statistics >>> data = [2.75, 1.75, 1.25, 0.25, 0.5, 1.25, 3.5] >>> statistics.mean(data) 1.6071428571428572 >>> statistics.median(data) 1.25 >>> statistics...
The python statistics.geometric_mean() function is an iterable function, that converts data to floats and calculates the geometric mean.If the function contains a zero or negative value, then this raises StatisticsError.SyntaxFollowing is the basic syntax of the statistics.geometric_mean() function...
This example shows how to create a function that calculates the mean of a sequence of numbers. The name of the function is getMean. There is a phrase between the opening and closing parentheses to represent the sequence of numbers being passed into the function—this is a variable that is ...
To illustrate, the example below shows a toy function that checks the length of a string object: Python >>> def validate_length(string): ... if (n := len(string)) < 8: ... print(f"Length {n} is too short, needs at least 8") ... else: ... print(f"Length {n} is...