Arcane.Analytics
Análise de dados: estatística, regressão, clustering e gráficos.
exemplo
adopt Arcane.Analytics as An
x := [1, 2, 3, 4, 5]
y := [2, 4, 6, 8, 10]
out round(An.correlation(x, y), 4)
out An.quartiles(x)
out An.outliers([10, 11, 12, 200])
modelo := An.linear_regression(x, y)
out round(modelo["slope"], 2), round(An.predict_linear(modelo, 6), 2)Funções (65)#
| Assinatura |
|---|
DataFrame(data=None, columns=None) |
autocorrelation(data, lag=1) |
bar_chart(data, labels=None, width=40, char='█') |
bin_data(data, bins=5) |
bootstrap(data, n_samples=1000, stat_fn=None) |
box_plot(data, width=40) |
correlation(x, y) |
correlation_matrix(data_dict) |
cosine_similarity(a, b) |
covariance(x, y) |
create_frame(data, columns=None) |
cross_tab(data, row_fn, col_fn) |
cumulative_sum(data) |
data_types(data) |
describe(data) |
diff(data, periods=1) |
euclidean_distance(a, b) |
exponential_smoothing(data, alpha=0.3) |
frequency_table(data) |
from_csv(path, delimiter=',', has_header=True) |
from_dict(d) |
from_json(path) |
from_records(records) |
group_by(data, key_fn) |
heatmap(matrix, row_labels=None, col_labels=None) |
histogram(data, bins=10, width=40, char='█') |
iqr(data) |
kmeans(data, k=3, max_iter=100) |
kurtosis(data) |
lag(data, k=1) |
line_chart(data, width=60, height=15) |
linear_regression(x, y) |
log_transform(data, base=None) |
manhattan_distance(a, b) |
mean(data) |
median(data) |
min_max_scale(data, feature_range=(0, 1)) |
missing_values(data) |
mode(data) |
moving_average(data, window=3) |
normalize(data, low=0, high=1) |
outliers(data, threshold=1.5) |
percentile(data, p) |
pivot_table(data, index_fn, value_fn, agg='sum') |
predict_linear(model, x_val) |
profile(data) |
quartiles(data) |
r_squared(x, y) |
rank(data, method='average') |
running_average(data) |
sample(data, n=5, replace=False) |
scatter_plot(x, y, width=40, height=20) |
seasonality(data, period=7) |
silhouette_score(data, labels) |
skewness(data) |
sparkline(data) |
standardize(data) |
stdev(data) |
stratified_sample(data, labels, n_per_group=2) |
summary(data) |
trend(data) |
unique_counts(data) |
value_counts(data) |
variance(data) |
zscore(data) |