Picking up column values based on two conditions

Question

I have the following text output, my goal is to only select values of column 2 when the values in column 1 are greater than 1 but less than or equal to 4. So I am looking for Python to print out Column 2 values as [-6,0,-4] because only these values meet the criteria of column 1.

1. 1 2
2. 2 -6
3. 3 0
4. 4 -4
5. 5 100

I tried the following approach.

import pandas as pd
import numpy as np
data= pd.read_table('/Users/Hrihaan/Desktop/A.txt', dtype=float, header=None, sep='\s+').values
x=data[:,0]
y=np.where(1< x<= 4, data[:, 1], np.nan)
print(y)

I received the following error: ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Any suggestion would be really helpful.

Answer 1

1st using .loc

df.loc[(df.a>1)&(df.a<=4), 'b']
Out[316]: 
1   -6
2    0
3   -4

2nd base on you own approach

np.where((df.a<= 4)&(df.a>1), df.b,np.nan)

Out[322]: array([ nan,  -6.,   0.,  -4.,  nan])

data input :

df = pd.DataFrame({"a":np.arange(1,6), "b":[2,-6,0,-4,100]})

Answer 2

There are a few ways to accomplish this with Pandas. One simple solution is to use query():

import pandas as pd
import numpy as np

data = {"a":np.arange(1,6), "b":[2,-6,0,-4,100]}
df = pd.DataFrame(data)

print(df)
   a    b
0  1    2
1  2   -6
2  3    0
3  4   -4
4  5  100

Now filter using query, and select column b:

df.query('1 < a <= 4').b

1   -6
2    0
3   -4
Name: b, dtype: int64