在包含大数据的 csv 文件上创建用户输入过滤器

Question

I have a program that open and read a file in csv format that contains large data such as:

State      Crime type Occurrences Year 

CALIFORNIA ROBBERY    12          1999
CALIFORNIA ASSAULT    45          2003
NEW YORK   ARSON      9           1999
CALIFORNIA ARSON      21          2000
TEXAS      THEFT      30          2000
OREGON     ASSAULT    10          2001

I need to create 3 filters by user input. For example:

Enter State:
Enter Crime Type:
Enter Year:

If I enter:

Enter State: CALIFORNIA
Enter Crime: ASSAULT
Enter Year:  2003

Crime Report
State      Crime type Occurrences Year
CALIFORNIA ASSAULT    45          2003

This needs to happen.

I have no clue on how to tackle this problem.. I was only able to open and read the data file in csv format into a table in Python that will just print out every line. However, I need to incorporate search filter to narrow the result such as shown above. Anyone familiar with this? Thank you all for your help.

Answer 1

The Pandas library in Python allows you to view and manipulate csv data. The following solution imports the pandas library, reads the csv using the read_csv() function and loads it into a dataframe, then ask for input values, keeping in mind that State and Crime should be string values and cast as str and Year should be integer and cast as int , then applies a simple query to filter the results you need from the dataframe. We build this query keeping in mind that all three conditions should be met and that the input strings can be lowercase too.

In [125]: import pandas as pd
In [126]: df = pd.read_csv('test.csv')

In [127]: df
Out[127]:
        State Crime type  Occurrences  Year
0  CALIFORNIA    ROBBERY           12  1999
1  CALIFORNIA    ASSAULT           45  2003
2    NEW YORK      ARSON            9  1999

In [128]: state = str(input("Enter State: "))
Enter State: California

In [129]: crime_type = str(input("Enter Crime Type: "))
Enter Crime Type: robbery

In [130]: year = int(input("Enter Year: "))
Enter Year: 1999

In [131]: df.loc[lambda x:(x['State'].str.lower().str.contains(state.lower()))
     ...: & (x['Crime type'].str.lower().str.contains(crime_type.lower())) & (x
     ...: ['Year'] == year)]
Out[131]:
        State Crime type  Occurrences  Year
0  CALIFORNIA    ROBBERY           12  1999