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Pandas DataFrame.describe()The describe() method is used for calculating some statistical data like percentile, mean and std of the numerical values of the Series or DataFrame. It analyzes both numeric and object series and also the DataFrame column sets of mixed data types. SyntaxDataFrame.describe(percentiles=None, include=None, exclude=None) Parameters
 ReturnsIt returns the statistical summary of the Series and DataFrame. Example1import pandas as pd import numpy as np a1 = pd.Series([1, 2, 3]) a1.describe() Output count 3.0 mean 2.0 std 1.0 min 1.0 25% 1.5 50% 2.0 75% 2.5 max 3.0 dtype: float64 Example2import pandas as pd import numpy as np a1 = pd.Series(['p', 'q', 'q', 'r']) a1.describe() Output count 4 unique 3 top q freq 2 dtype: object Example3
import pandas as pd
import numpy as np
a1 = pd.Series([1, 2, 3])
a1.describe()
a1 = pd.Series(['p', 'q', 'q', 'r'])
a1.describe()
info = pd.DataFrame({'categorical': pd.Categorical(['s','t','u']),
'numeric': [1, 2, 3],
'object': ['p', 'q', 'r']
 })
info.describe(include=[np.number])
info.describe(include=[np.object])
info.describe(include=['category'])
Output categorical count 3 unique 3 top u freq 1 Example4
import pandas as pd
import numpy as np
a1 = pd.Series([1, 2, 3])
a1.describe()
a1 = pd.Series(['p', 'q', 'q', 'r'])
a1.describe()
info = pd.DataFrame({'categorical': pd.Categorical(['s','t','u']),
'numeric': [1, 2, 3],
'object': ['p', 'q', 'r']
 })
info.describe()
info.describe(include='all')
info.numeric.describe()
info.describe(include=[np.number])
info.describe(include=[np.object])
info.describe(include=['category'])
info.describe(exclude=[np.number])
info.describe(exclude=[np.object])
Output categorical numeric count 3 3.0 unique 3 NaN top u NaN freq 1 NaN mean NaN 2.0 std NaN 1.0 min NaN 1.0 25% NaN 1.5 50% NaN 2.0 75% NaN 2.5 max NaN 3.0 
Next TopicDataFrame.drop_duplicates()
 
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