titaneric/data.csv

## data.csv

          
            A
            B
            C
            D

            
              1
              2
              3
              4

            
              2
              3
              4
              5

            
              5
              6
              7
              8

            
              2
              3
              4
              6

## ptt.py
import numpy as np
import pandas as pd

df = pd.read_csv("data.csv")

# find rows that "A" column is 1
print(df[df["A"] == 1])

# find rows that "A" column is in [1, 2]
q = [1, 2]
print(df[df["A"].isin(q)])

# more flexible filter
keys = ["A", "B"]
values = [1, 3]
condition = np.array([
    (df[k] == v).values for k, v in zip(keys, values)
])
print(condition)
mask = np.logical_or.reduce(condition)
print(mask)
print(df[mask])
	import numpy as np
	import pandas as pd

	df = pd.read_csv("data.csv")

	# find rows that "A" column is 1
	print(df[df["A"] == 1])

	# find rows that "A" column is in [1, 2]
	q = [1, 2]
	print(df[df["A"].isin(q)])

	# more flexible filter
	keys = ["A", "B"]
	values = [1, 3]
	condition = np.array([
	(df[k] == v).values for k, v in zip(keys, values)
	])
	print(condition)
	mask = np.logical_or.reduce(condition)
	print(mask)
	print(df[mask])