如何使用输入数字提取 dataframe 中的行？

Question

I am extracting rows based on input of a column header and a value. For example, to extract data rows for all 'bmw' under 'company.

I can do this under strings (eg bmw, mercedes under 'company') but not numbers (eg '111' under horsepower).

I tried to change numbers like '111' to string but to no avail.

Sorry for the bad formatting, learning the platform.

Any help is appreciated!

Part of my data is:

import pandas as pd
import numpy as np

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

column1_title = input("Hi! Please enter the first column name you are searching for: ")
column1_title = column1_title.lower()

def extract(column_check):
    if np.any(column_check == df.columns):
        column1_value = input("Thank you. Please enter the value you are looking for under this name: ")
        column1_value = str(column1_value.lower())

        if np.any(column1_value == df[column_check]):
            print("You have entered:", column1_value) #feedback.
            print(df.loc[df[column_check] == column1_value]) #M2

    elif column_check.lower() == "exit":
            print("Thank you. Goodbye.")

extract(column1_title)

Answer 1

Since you are making the user input a string type, you should convert any Series you are checking to a string type by using the .astype(str) method:

import pandas as pd
import numpy as np

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

column1_title = input("Hi! Please enter the first column name you are searching for: ")
column1_title = column1_title.lower()

def extract(column_check):
    if np.any(column_check == df.columns):
        column1_value = input("Thank you. Please enter the value you are looking for under this name: ")
        column1_value = str(column1_value.lower())

        ## change this block
        if np.any(column1_value == df[column_check].astype(str)):
            print("You have entered:", column1_value) #feedback.
            print(df.loc[df[column_check].astype(str) == column1_value]) #M2

    elif column_check.lower() == "exit":
            print("Thank you. Goodbye.")

extract(column1_title)

Example output from the command line:

>>> df = pd.DataFrame({'a':[1,2],'b':['a','b']})
>>> extract('a')
Thank you. Please enter the value you are looking for under this name: 1
You have entered: 1
   a  b
0  1  a