Filtering Rows Of A Dataframe Based On Values In Columns

I want to filter the rows of a dataframe that contains values less than ,say 10. import numpy as np import pandas as pd from pprint import pprint df = pd.DataFrame(np.random.randin

Solution 1:

Use:

np.random.seed(21)
df = pd.DataFrame(np.random.randint(0,100,size=(10, 4)), columns=list('ABCD'))

If want filter by any value of condition, is necessary add DataFrame.any for test at least one True of boolean DataFrame:

df1 = df[(df < 10).any(axis=1)]
print (df1)
    A   B   C   D
0  73  79  56   4
5   5  18  70  50
7   5  80  35  91
9   6  84  90  28

---

print (df < 10)
       A      B      C      D
0FalseFalseFalseTrue1FalseFalseFalseFalse2FalseFalseFalseFalse3FalseFalseFalseFalse4FalseFalseFalseFalse5TrueFalseFalseFalse6FalseFalseFalseFalse7TrueFalseFalseFalse8FalseFalseFalseFalse9TrueFalseFalseFalseprint ((df < 10).any(axis=1))
0True1False2False3False4False5True6False7True8False9True
dtype: bool