J
If I understand the vc question only needs a mask, see:import pandas as pd
a = [[1,2,'n/a'],[2,1,'n/a'],[3,4,'n/a'],[4,3,'n/a']]
candles = pd.DataFrame(a,columns=['askclose', 'askopen', 'fechamento'])
print('Candles original', candles, sep='\n')
Candle original
askclose askopen fechamento
0 1 2 n/a
1 2 1 n/a
2 3 4 n/a
3 4 3 n/a
Criação da mascara
mask = candles.askopen>candles.askclose
Atualização do candles
candles.loc[mask, 'fechamento'] = 'alta'
print('Candles atualizado', candles, sep='\n')
Candles atualizado
askclose askopen fechamento
0 1 2 alta
1 2 1 n/a
2 3 4 alta
3 4 3 n/a
Note:To assign a different value when askopen for smaller, create a second mask or deny the mask created with a bitwise operator (candles.loc[~mask, 'fechamento'] = 'baixa') https://repl.it/@sidonduarte/pandas-mask-1 Edit After your issue to the question I understood that your need is to iterate the dataframe, I created a function that iterates the df received and changes it based on the previous value of a column, to simplify I used numerical values and column names based on the first 3 letters (a, b, c). Just adapt to your need.import pandas as pd
import numpy as np
def iter_df(df):
for i in range(0, len(df)):
if i !=0:
print('indice atual: ',i, 'coluna: a')
print('valor atual :', df.iloc[i]['a'], 'valor anterior: ',
df.iloc[i-1]['a'])
print('-'*36)
# Alterando o valor de uma coluna baseado no valor do indice anterior
if df.iloc[i-1]['a']==11:
df.iloc[i]['a']=99
return df
a = np.array([[1, 2, 3], [11, 12, 13], [21, 22, 23], [31, 32, 33], [41, 42, 43]])
df = pd.DataFrame(a, columns=['a', 'b', 'c'])
print ('df antes da atualizacao', df, sep='\n')
df antes da atualizacao
a b c
0 1 2 3
1 11 12 13
2 21 22 23
3 31 32 33
4 41 42 43
print ('df pós atualizacao', iter_df(df),sep='\n' )
indice atual: 1 coluna: a
valor atual : 11 valor anterior: 1
indice atual: 2 coluna: a
valor atual : 21 valor anterior: 11
indice atual: 3 coluna: a
valor atual : 31 valor anterior: 21
indice atual: 4 coluna: a
valor atual : 41 valor anterior: 31
df pós atualizacao
a b c
0 1 2 3
1 11 12 13
2 99 22 23
3 31 32 33
4 41 42 43
Look at that. https://repl.it/@sidonduarte/pandas-iter-rows-2
