Python | Pandas Panel.clip_upper ()

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Panel.clip_upper() viene utilizzato per restituire una copia dell’input con valori troncati superiori ai valori specificati.

Sintassi: Panel.clip_upper (soglia, asse = Nessuno, inplace = False)

Parametri: < br /> soglia: float o array_like
asse: Allinea l’oggetto con la soglia lungo l’asse specificato.
inplace: Se eseguire l’operazione in place sui dati

Restituisce: stesso tipo di input.

Creazione del pannello:

# importazione modulo pandas

import panda come pd

import numpy as np

df1 = pd.DataFrame ({ ’a’ : [ ’Geek’ , ’ For’ , ’geek’ ],

’b’ : np.random.randn ( 3 )})

data = { ’ item1’ : df1, ’item2’ : df1}


# crea un pannello

pannello = pd.Panel.from_dic t (data, orient = ’minore’ )

print (riquadro, code> "" )

< p>

Esci :

Codice n. 1: Utilizzo di clip_upper()

# panda module import

import panda come pd

import numpy come np

< /p>

df1 = pd.DataFrame ({ ’a’ : [ ’Geek’ , ’ For’ , ’geek’ ],

’b’ : np.random.correva dn ( 3 )})

< p> dati = { ’ item1’ : df1, ’item2’ : df1}


# crea un pannello

pannello = pd.Panel.from_dict (dati, orienta = ’minore’ )

print (riquadro, "" )

print (pannello [ ’b’ ], < codice classe = "string"> ’’ )

df2 = pd.DataFrame ({ ’b’ : np.random.randn ( 5 )})

print (pannello [ ’b’ ] .clip_upper (df2 [ ’b’ ], asse = 0 ))

Output:

Codice n. 2: Utilizzo di clip_upper ()

< p>

# crea un pannello vuoto

import panda come pd

import numpy as np

dati = { ’ Item1’ : pd.DataFrame (np. casuale.randn ( 7 , 4 )),

’Item2’ : pd.DataFrame (np.random.randn ( 4 , 5 ))}

penna = pd.Panel (data)

print (penna [ ’Item1’ ], ’ ’ )

p = penna [ ’ Item1’ ] [ 0 ]. clip_upper (np.random.randn ( 7 ))

print (p)

Output:

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