如何獲取 csv 列中的出現次數並保存為包含 python 中的計數的新 csv

Question

我是 python 的新手，非常感謝您的幫助。 我嘗試了一整天。 我有一個包含 10 列的 csv 文件。 我只對 3 state、縣和郵政編碼感興趣。 我正在嘗試，嘗試並嘗試計算每列中出現的次數，例如 CA 20000、TX 14000，並將計數結果輸出保存在 csv 文件中，該文件可以輕松導入 excel 並進一步與地理空間合並文件。

我設法 select 我需要的 3 列

import numpy as np

from tabulate import tabulate

import pandas as pd 


#Replace with path and name file in your computer
filename = "10column.csv"

# Enter the column number that you want to display between [, , ,] no space between the commas  "usecols=[3,4,5]" 
table = np.genfromtxt(filename,delimiter=',',skip_header=0,dtype='U',usecols=[4,5,6])

print(tabulate(table))

#Insert the path and name of the file 
pd.DataFrame(table).to_csv("3column.csv") 

然后我嘗試計算出現次數，但 output 格式錯誤，我無法保存為 csv。

import csv

from collections import Counter


import numpy as np

my_reader = csv.reader(open("3column.csv"))

#insert column number instead of the 2 "[rec[2]"
column = [rec[2] for rec in my_reader]

np.array([Counter(column)])

print(np.array([Counter(column)]))

結果是

[Counter({'22209': 10, '20007': 5, …'})]

我無法將其保存為 csv 並且我想使用表格格式

zip, count
22209, 10, 20007, 10

我將衷心感謝您的幫助

Answer 1

另一種方法是使用 Pandas 文檔中的value_counts() 。

返回一個包含唯一值計數的系列。

示例數據文件7column.csv

id,state,city,zip,ip_address,latitude,longitude
1,NY,New York City,10005,246.78.179.157,40.6964,-74.0253
2,WA,Yakima,98907,79.61.127.155,46.6288,-120.574
3,OK,Oklahoma City,73109,129.226.225.133,35.4259,-97.5261
4,FL,Orlando,32859,104.196.5.159,28.4429,-81.4026
5,NY,New York City,10004,246.78.180.157,40.6964,-74.0253
6,FL,Orlando,32860,104.196.5.159,29.4429,-81.4026
7,IL,Chicago,60641,19.226.187.13,41.9453,-87.7474
8,NC,Fayetteville,28314,45.109.1.38,35.0583,-79.008
9,IL,Chicago,60642,19.226.187.14,41.9453,-87.7474
10,WA,Yakima,98907,79.61.127.156,46.6288,-120.574
11,IL,Chicago,60643,19.226.187.15,41.9453,-87.7474
12,CA,Sacramento,94237,77.208.31.167,38.3774,-121.4444

import pandas as pd

df = pd.read_csv("7column.csv")

zipcode = df["zip"].value_counts()
state = df["state"].value_counts()
city = df["city"].value_counts()

zipcode.to_csv('zipcode_count.csv')
state.to_csv('state_count.csv')
city.to_csv('city_count.csv')

CSV output 文件

state_count.csv   |   city_count.csv      |  zipcode_count.csv
,state            |   ,city               |  ,zip
IL,3              |   Chicago,3           |  98907,2
NY,2              |   Orlando,2           |  32859,1
FL,2              |   New York City,2     |  94237,1
WA,2              |   Yakima,2            |  32860,1
NC,1              |   Sacramento,1        |  28314,1
OK,1              |   Fayetteville,1      |  10005,1
CA,1              |   Oklahoma City,1     |  10004,1
                  |                       |  60643,1
                  |                       |  60642,1
                  |                       |  60641,1
                  |                       |  73109,1

Answer 2

您可以以 DataFrame 的形式讀取您寫給 CSV 的文件，並使用 Pandas 具有的計數方法。

states_3 = pd.DataFrame(table)

state_count = states_3.count(axis='columns')

out_name = 'statecount.xlsx'
with pd.ExcelWriter(out_name) as writer:
    state_count.to_excel(writer, sheet_name='counts')