I'm trying set a upper bound and lower bound based out of user input where upper bound is userinput 10

create DataFrame

df = pd.DataFrame({
    'VIN':['v1', 'v1', 'v1', 'v1', 'v1', 'v2', 'v2', 'v2', 'v2', 'v2'],
    'Revenue':[30, 50, 40, 30, 40, 30, 50, 40, 30, 50], 
    'Category':['MKL', 'GKL','GKL', 'UKL', 'MKL', 'MKL', 'GKL', 'GKL', 'UKL', 'MKL'],
    'Age':[64, 41, 54, 63, 64, 63, 53, 42, 32, 61]
})
print(df)

  VIN  Revenue Category     Age
0  v1       30      MKL     64
1  v1       50      GKL     41
2  v1       40      GKL     54
3  v1       30      UKL     63
4  v1       40      MKL     64
5  v2       30      MKL     63
6  v2       50      GKL     53
7  v2       40      GKL     42
8  v2       30      UKL     32
9  v2       50      MKL     61

i tried below code but getting error of : ('Lengths must match to compare', (995,), (1,)):

Age1 = [int(x) for x in input('Please enter Age?= ').split(',')]
dummy=[10]
t2=[x   y for x, y in zip(Age1, dummy)]
df = df[(df['Age'] >= Age1) & (df['Age'] <= t2)]

CodePudding user response：

The problem is storing the values in lists and accessing these, after changing the query to access the list value through Age1[0] (the first and only value in the list), the value is correctly stored. Your zip function also ceased working as you need to include the columns in square brackets like [Age1]. In each case you should specify to take the first value from the list you are storing the results in using [0].

The code works for me with the following additions:

import pandas as pd
df = pd.DataFrame({
    'VIN':['v1', 'v1', 'v1', 'v1', 'v1', 'v2', 'v2', 'v2', 'v2', 'v2'],
    'Revenue':[30, 50, 40, 30, 40, 30, 50, 40, 30, 50], 
    'Category':['MKL', 'GKL','GKL', 'UKL', 'MKL', 'MKL', 'GKL', 'GKL', 'UKL', 'MKL'],
    'Age':[64, 41, 54, 63, 64, 63, 53, 42, 32, 61]
})

Age1 = [int(x) for x in input('Please enter Age?= ').split(',')]
dummy=[10]
t2=[x   y for x, y in zip([Age1[0]], [dummy[0]])]
df = df[(df['Age'] >= Age1[0]) & (df['Age'] <= t2[0])]

print(Age1)
print(df)

[60]
  VIN  Revenue Category  Age
0  v1       30      MKL   64
3  v1       30      UKL   63
4  v1       40      MKL   64
5  v2       30      MKL   63
9  v2       50      MKL   61