beach water quality

from tabulight import EDA
from tabulight import wq_data
from tabulight.utils import print_info

# sphinx_gallery_thumbnail_number = 7

print_info()

numpy 2.3.4
pandas 2.3.3
tabulight 0.1.0
python 3.12.10 (main, May  6 2025, 10:49:23) [GCC 11.4.0]
os posix
matplotlib 3.10.7
scipy 1.16.2
seaborn 0.13.2
statsmodels 0.14.5
Script Executed on:  18 October 2025 18:28:05
tot_cpus 2
avail_cpus 2
mem_gib 7.555534362792969

data = wq_data(target=['ecoli', 'sul1_coppml', 'aac_coppml',
                           'tetx_coppml', 'blaTEM_coppml'])
print(data.shape)

(1446, 18)

data.head()

	tide_cm	wat_temp_c	sal_psu	air_temp_c	pcp_mm	pcp3_mm	pcp6_mm	pcp12_mm	wind_dir_deg	wind_speed_mps	air_p_hpa	mslp_hpa	rel_hum	ecoli	sul1_coppml	aac_coppml	tetx_coppml	blaTEM_coppml
index
2018-06-19 00:00:00	36.407149	19.321232	33.956058	19.780000	0.0	0.0	0.0	0.0	159.533333	0.960000	1002.856667	1007.256667	95.000000	NaN	NaN	NaN	NaN	NaN
2018-06-19 00:30:00	35.562515	19.320124	33.950508	19.093333	0.0	0.0	0.0	0.0	86.596667	0.163333	1002.300000	1006.700000	95.000000	NaN	NaN	NaN	NaN	NaN
2018-06-19 01:00:00	34.808016	19.319666	33.942532	18.733333	0.0	0.0	0.0	0.0	2.260000	0.080000	1001.973333	1006.373333	95.000000	NaN	NaN	NaN	NaN	NaN
2018-06-19 01:30:00	30.645216	19.320406	33.931263	18.760000	0.0	0.0	0.0	0.0	62.710000	0.193333	1001.776667	1006.120000	95.006667	NaN	NaN	NaN	NaN	NaN
2018-06-19 02:00:00	26.608980	19.326729	33.917961	18.633333	0.0	0.0	0.0	0.0	63.446667	0.510000	1001.743333	1006.103333	95.006667	NaN	NaN	NaN	NaN	NaN

data.isna().sum()

tide_cm              0
wat_temp_c           0
sal_psu              0
air_temp_c           0
pcp_mm               0
pcp3_mm              0
pcp6_mm              0
pcp12_mm             0
wind_dir_deg         0
wind_speed_mps       0
air_p_hpa            0
mslp_hpa             0
rel_hum              0
ecoli             1279
sul1_coppml       1228
aac_coppml        1228
tetx_coppml       1228
blaTEM_coppml     1228
dtype: int64

data.isna().sum()

tide_cm              0
wat_temp_c           0
sal_psu              0
air_temp_c           0
pcp_mm               0
pcp3_mm              0
pcp6_mm              0
pcp12_mm             0
wind_dir_deg         0
wind_speed_mps       0
air_p_hpa            0
mslp_hpa             0
rel_hum              0
ecoli             1279
sul1_coppml       1228
aac_coppml        1228
tetx_coppml       1228
blaTEM_coppml     1228
dtype: int64

eda = EDA(data, save=False)

eda.data_availability()

/home/docs/checkouts/readthedocs.org/user_builds/tabulight/checkouts/latest/tabulight/_main.py:347: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  im.axes.set_xticklabels(

<Figure size 950x1180 with 1 Axes>

_ = eda.plot_missing()

/home/docs/checkouts/readthedocs.org/user_builds/tabulight/checkouts/latest/tabulight/_main.py:444: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax1.set_yticklabels(ax1.get_yticks(), fontsize="18")

# _ = eda.plot_data(subplots=True, max_cols_in_plot=20, figsize=(14, 20))
#
# ###########################################################

_ = eda.plot_data(subplots=True, max_cols_in_plot=20, figsize=(14, 20),
              ignore_datetime_index=True)

_ = eda.plot_histograms()

_ = eda.box_plot(max_features=18, palette="Set3")

/home/docs/checkouts/readthedocs.org/user_builds/tabulight/checkouts/latest/tabulight/_main.py:1424: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  axis.set_xticklabels(list(data.columns), fontdict={'rotation': 70})

eda.box_plot(max_features=18, palette="Set3", violen=True)

/home/docs/checkouts/readthedocs.org/user_builds/tabulight/checkouts/latest/tabulight/_main.py:1424: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  axis.set_xticklabels(list(data.columns), fontdict={'rotation': 70})

<Axes: >

eda.correlation(figsize=(14, 14))

# ###########################################################
#
#
# eda.grouped_scatter(max_subplots=18)

<Axes: >

_ = eda.autocorrelation(n_lags=15)

cannot plot autocorrelation for ecoli feature
cannot plot autocorrelation for sul1_coppml feature
cannot plot autocorrelation for aac_coppml feature

_ = eda.partial_autocorrelation(n_lags=15)

cannot plot autocorrelation for ecoli feature
cannot plot autocorrelation for sul1_coppml feature
cannot plot autocorrelation for aac_coppml feature

_ = eda.lag_plot(n_lags=14, s=0.4)

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_ = eda.plot_ecdf(figsize=(10, 14))

eda.normality_test()