Reputation: 103
I need to convert this big if statement from python to python pandas. I have a problem because inside of this statement have a multiple if statements.
All values (x_value, i_value, u_value, y_val, tb, uvd
) are columns in xlsx sheet. I need to create a new column with codes that are in print function. Statement is a longer than is showed here
import math
if x_value <= 1.00 and x_value >= 0:
if y_val <= 0.25 and y_val >= 0:
if tb < 0 and i_value == 0:
print('aa1')
elif tb < 0 and uvd > 0:
print('aa2')
elif tb < 0 and uvd < 0:
print('aa3')
elif tb > 0 and uvd < 0:
print('aa4')
elif tb > 0 and uvd > 0:
print('aa5')
elif tb > 0 and u_value > 0:
print('aa6')
else:
print('error')
elif y_val <= 0.50 and y_val >= 0.25:
if tb < 0 and i_value == 0:
print('ab1')
elif tb < 0 and uvd > 0:
print('ab2')
elif tb < 0 and uvd < 0:
print('ab3')
elif tb > 0 and uvd < 0:
print('ab4')
elif tb > 0 and uvd > 0:
print('ab5')
elif tb > 0 and u_value > 0:
print('ab6')
else:
print('error')
elif y_val <= 0.75 and y_val >= 0.50:
if tb < 0 and i_value == 0:
print('ac1')
elif tb < 0 and uvd > 0:
print('ac2')
elif tb < 0 and uvd < 0:
print('ac3')
elif tb > 0 and uvd < 0:
print('ac4')
elif tb > 0 and uvd > 0:
print('ac5')
elif tb > 0 and u_value > 0:
print('ac6')
else:
print('error')
elif y_val <= 1.00 and y_val >= 0.75:
if tb < 0 and i_value == 0:
print('ad1')
elif tb < 0 and uvd > 0:
print('ad2')
elif tb < 0 and uvd < 0:
print('ad3')
elif tb > 0 and uvd < 0:
print('ad4')
elif tb > 0 and uvd > 0:
print('ad5')
elif tb > 0 and u_value > 0:
print('ad6')
else:
print('error')
else:
print('Error!')
elif x_value <= 3.00 and x_value >= 1:
if y_val <= 0.25 and y_val >= 0:
if tb < 0 and i_value == 0:
print('ba1')
elif tb < 0 and uvd > 0:
print('ba2')
elif tb < 0 and uvd < 0:
print('ba3')
elif tb > 0 and uvd < 0:
print('ba4')
elif tb > 0 and uvd > 0:
print('ba5')
elif tb > 0 and u_value > 0:
print('ba6')
else:
print('error')
elif y_val <= 0.50 and y_val >= 0.25:
if tb < 0 and i_value == 0:
print('bb1')
elif tb < 0 and uvd > 0:
print('bb2')
elif tb < 0 and uvd < 0:
print('bb3')
elif tb > 0 and uvd < 0:
print('bb4')
elif tb > 0 and uvd > 0:
print('bb5')
elif tb > 0 and u_value > 0:
print('bb6')
else:
print('error')
elif y_val <= 0.75 and y_val >= 0.50:
if tb < 0 and i_value == 0:
print('bc1')
elif tb < 0 and uvd > 0:
print('bc2')
elif tb < 0 and uvd < 0:
print('bc3')
elif tb > 0 and uvd < 0:
print('bc4')
elif tb > 0 and uvd > 0:
print('bc5')
elif tb > 0 and u_value > 0:
print('bc6')
else:
print('error')
elif y_val <= 1.00 and y_val >= 0.75:
if tb < 0 and i_value == 0:
print('bd1')
elif tb < 0 and uvd > 0:
print('bd2')
elif tb < 0 and uvd < 0:
print('bd3')
elif tb > 0 and uvd < 0:
print('bd4')
elif tb > 0 and uvd > 0:
print('bd5')
elif tb > 0 and u_value > 0:
print('bd6')
else:
print('error')
else:
print('Error!')
else:
print('ERROR')
Any suggestions?
Upvotes: 2
Views: 95
Reputation: 1968
import numpy as np
import pandas as pd
data = pd.DataFrame(np.random.random(size=(10, 6)))
data.columns = ['x_value', 'i_value', 'u_value', 'y_val', 'tb', 'uvd']
data
def cal_value(x):
if x['x_value'] < 0.5 and x['y_val'] > 0.5:
return 'type1'
elif x['i_value'] < 0.5 and x['tb'] > 0.5:
return 'type2'
else:
return 'type3'
apply
function in DataFramedata['type'] = data.apply(lambda x: cal_value(x), axis=1)
data
if want get more detail about apply
, click pandas documents link: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html
Upvotes: 2