Analyze and Visualize your data with Jupyter Notebook¶

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()
%matplotlib inline

data = pd.read_json("https://citizenscience.gcoos.org/openapi/v1/natures_academy/data")
data.head()

data.info()

numeric_columns = ['No', 'Site_ID', 'Participants','AirTemp_C', 'Wind_Speed_mph',
               'Tide_stage', 'WaterTemp_C', 'Salinity_ppt', 'Turbidity_NTU', 'pH',
               'DissolvedOxygen_ppm', 'Nitrates_ppm', 'Litter_kg']
data[numeric_columns] = data[numeric_columns].apply(pd.to_numeric, errors='coerce')
data.info()

sns.lineplot(data=data, x="Date_Time",y="WaterTemp_C", markers=True, dashes=False);

sns.distplot(data["WaterTemp_C"]);

data_pair = data_num.drop(["No","Site_ID"], axis=1)
g = sns.pairplot(data_pair)