如何在python中迭代两列？

Question

im trying to iterate through two columns in the csv file using python?, I heard that you have to import pandas for this, but im just struggling on the coding part.

import csv as csv
import numpy as np
import pandas as pd

csv_file_object = csv.reader(open('train.csv', 'rb'))  # Load in the csv file
header = csv_file_object.next()                   # Skip the fist line as it is a header
data=[]                                     # Create a variable to hold the data

for row in csv_file_object:                      # Skip through each row in the csv file,
    data.append(row[0:])                        # adding each row to the data variable
data = np.array(data)   



def number_of_female_in_class_3(data):
    for row in data.iterow:
        if row[2] == 'female' and row[4] == '3':
            sum += 1

The problem is the function number_of_female_in_class_3 i want to go through two colunms, i want to go through column 2 to check if the rows contains the string 'female' and go through columns 4 and check if the status is '3'.If this is true then i want to increment 1 to sum .

I was wondering if someone can post a simple code on how to accomplish this?

here is the train.csv file im trying to retrieve.

**PassengerID** | **Survived** | **Pclass**   | **Name**  |  **Sex**   |
          1     |          0   |         3    |  mary     |  Female    |
          2     |          1   |         2    |  james    |  Male      |
          3     |          1   |         3    |  Tanya    |  Female    |

Thank you

Answer 1

Indeed, pandas can help you here.

I'm starting with a cleaner CSV:

PassengerID,Survived,Pclass,Name,Sex
1,0,3,mary,female
2,1,2,james,male
3,1,3,tanya,female

If your CSV actually looks like what you posted (not really a CSV), then you will have some wrangling to do (see below). But if you can get pandas to eat it:

>>> import pandas as pd
>>> df = pd.DataFrame.from_csv('data.csv')
>>> result = df[(df.Sex=='female') & (df.Survived==False)]

Results in a new DataFrame :

>>> result
             Survived  Pclass  Name     Sex
PassengerID                                
1                   0       3  mary  female

You can do len(result) to get the count you're after.

---

Loading that CSV

If you're stuck with that nasty CSV, you can get your df like so:

# Load using a different delimiter.
df = pd.DataFrame.from_csv('data.csv', sep="|")

# Rename the index.
df.index.names = ['PassID']

# Rename the columns, using X for the bogus one.
df.columns = ['Survived', 'Pclass', 'Name', 'Sex', 'X']

# Remove the 'extra' column.
del df['X']

Answer 2

I think this is what you need:

import csv

def number_of_female_in_class_3(data):
    # initialize sum variable
    sum = 0
    for row in data:
        if row[4] == 'Female' and row[2] == '3':
            # match
            sum += 1
    # return the result
    return sum

# Load in the csv file
csv_file_object = csv.reader(open('train.csv', 'rb'), delimiter='|')
# skip the header
header = csv_file_object.next()
data = []

for row in csv_file_object:
    # add each row of data to the data list, stripping excess whitespace
    data.append(map(str.strip, row))

# print the result
print number_of_female_in_class_3(data)

Some explanation:

First of all in your file you have Female with an uppercase F, secondly you had your column numbers backwards (gender in column 5 and class in column 3) You need to initialize the sum variable to 0 before you start incrementing it. numpy and pandas are not needed here although you need to apply the strip function to every element in each row to remove excess spaces ( map(str.strip, row) ) and also pass delimiter='|' into csv.reader because the default delimiter is a comma. Lastly you need to return sum at the end of you function.