使用简单代码获取csv文件中整个列的平均值（Python）

我见过类似的问题，但从来没有一个能给出简单明了的蟒蛇式答案

我只是想得到csv文件中“high”列的平均值

import csv
import numpy as np    


with open('2010-Jan-June.csv', 'r', encoding='utf8', newline='') as f:
    highs = []
    for row in csv.DictReader(f, delimiter=','):
        high = int(row['high'])
print(sum(highs)/len(highs))

我的csv如下所示：

date,high,low,precip
1-Jan,43,41,0
2-Jan,50,25,0
3-Jan,51,25,0
4-Jan,44,25,0
5-Jan,36,21,0
6-Jan,39,20,0
7-Jan,47,21,0.04
8-Jan,30,14,0
9-Jan,30,12,0

使用熊猫：

import pandas as pd

avg = pd.read_csv(r'/path/to/2010-Jan-June.csv', usecols=['high'], squeeze=True).mean()

使用熊猫：

import pandas as pd

avg = pd.read_csv(r'/path/to/2010-Jan-June.csv', usecols=['high'], squeeze=True).mean()

---

注意，使用普通Python完全可以做到这一点：

import csv
import statistics as stats

with open('2010-Jan-June.csv') as f:
    avg = stats.mean(row['high'] for row in csv.DictReader(f, delimiter=','))

print(avg)

---

注意，使用普通Python完全可以做到这一点：

import csv
import statistics as stats

with open('2010-Jan-June.csv') as f:
    avg = stats.mean(row['high'] for row in csv.DictReader(f, delimiter=','))

print(avg)

---

因为您导入了

numpy

，所以您可以使用它-几乎和

pandas

一样简单：

从样本的粘贴副本中读取：

In [36]: txt="""date,high,low,precip
    ...: 1-Jan,43,41,0
    ...: 2-Jan,50,25,0
    ...: 3-Jan,51,25,0
    ...: 4-Jan,44,25,0
    ...: 5-Jan,36,21,0
    ...: 6-Jan,39,20,0
    ...: 7-Jan,47,21,0.04
    ...: 8-Jan,30,14,0
    ...: 9-Jan,30,12,0"""

带有numpy 1.14的Python3喜欢使用

编码

参数：

In [38]: data = np.genfromtxt(txt.splitlines(),delimiter=',',dtype=None,names=True,
    ...: encoding=None)
In [39]: data
Out[39]: 
array([('1-Jan', 43, 41, 0.  ), ('2-Jan', 50, 25, 0.  ),
       ('3-Jan', 51, 25, 0.  ), ('4-Jan', 44, 25, 0.  ),
       ('5-Jan', 36, 21, 0.  ), ('6-Jan', 39, 20, 0.  ),
       ('7-Jan', 47, 21, 0.04), ('8-Jan', 30, 14, 0.  ),
       ('9-Jan', 30, 12, 0.  )],
      dtype=[('date', '<U5'), ('high', '<i8'), ('low', '<i8'), ('precip', '<f8')])

或者在一行中，仅加载一列：

In [44]: np.genfromtxt(txt.splitlines(),delimiter=',',skip_header=1,usecols=[1]).mean()
Out[44]: 41.111111111111114

---

因为您导入了

numpy

，所以您可以使用它-几乎和

pandas

一样简单：

从样本的粘贴副本中读取：

In [36]: txt="""date,high,low,precip
    ...: 1-Jan,43,41,0
    ...: 2-Jan,50,25,0
    ...: 3-Jan,51,25,0
    ...: 4-Jan,44,25,0
    ...: 5-Jan,36,21,0
    ...: 6-Jan,39,20,0
    ...: 7-Jan,47,21,0.04
    ...: 8-Jan,30,14,0
    ...: 9-Jan,30,12,0"""

带有numpy 1.14的Python3喜欢使用

编码

参数：

In [38]: data = np.genfromtxt(txt.splitlines(),delimiter=',',dtype=None,names=True,
    ...: encoding=None)
In [39]: data
Out[39]: 
array([('1-Jan', 43, 41, 0.  ), ('2-Jan', 50, 25, 0.  ),
       ('3-Jan', 51, 25, 0.  ), ('4-Jan', 44, 25, 0.  ),
       ('5-Jan', 36, 21, 0.  ), ('6-Jan', 39, 20, 0.  ),
       ('7-Jan', 47, 21, 0.04), ('8-Jan', 30, 14, 0.  ),
       ('9-Jan', 30, 12, 0.  )],
      dtype=[('date', '<U5'), ('high', '<i8'), ('low', '<i8'), ('precip', '<f8')])

或者在一行中，仅加载一列：

In [44]: np.genfromtxt(txt.splitlines(),delimiter=',',skip_header=1,usecols=[1]).mean()
Out[44]: 41.111111111111114

---

这里是我尝试在一个pythonic答案只使用csv库

import csv
with open ('names.csv') as csvfile:
    reader = csv.DictReader(csvfile)
    print sum(float(d['high']) for d in reader) / (reader.line_num - 1)

---

如果文件中没有行，则将有一个除以0的值。

以下是我仅使用csv库的pythonic答案的尝试

import csv
with open ('names.csv') as csvfile:
    reader = csv.DictReader(csvfile)
    print sum(float(d['high']) for d in reader) / (reader.line_num - 1)

---

如果文件中没有行，则将有一个除以0的值。

+这是我的错+1将

high=int（row['high']）

更改为

high。追加（int（row['high']）

在

high\u avgs（）前面放一个
def
：

@PaulPanzer它实际上就在那里。我想把代码从我的函数框中拿出来。将

high=int（row['high']）

更改为

highs。追加（int（row['high']）

在

high\u avgs（）前面放一个
def
，它实际上就在那里。我想把代码从我的功能盒中拿出来。