如何导入CSV以分离变量以便对Matplotlib条形图进行“计数”
如何导入CSV以分离变量以便对Matplotlib条形图进行“计数”
提问于 2018-06-04 03:34:14
我目前正在对CSV文件编写一些描述性分析。
我想做的是；在CSV文件中创建位置出现的条形图，并绘制到条形图。
我想知道是否有一种方法可以将“许多”不同的位置作为单独的变量导入，因为当正则表达式与CSV匹配时，我需要为每个变量加1。
CSV列被称为；(为了方便起见，有些列被缩写为变量)
自治市：
COL = 0
Barnet = 0
Bexley = 0
BAD = 0
Brent = 0
Bromley = 0
Camden = 0
Croydon = 0
Ealing = 0
Enfield = 0
Greenwich = 0
Hackney = 0
HAF = 0
Haringey = 0
Harrow = 0
Havering = 0
Hillingdon = 0
Hounslow = 0
Islington = 0
KAC = 0
KUT = 0
Lambeth = 0
Lewisham = 0
Merton = 0
Newham = 0
Redbridge = 0
RUT = 0
Southwark = 0
Sutton = 0
TowerHamlets = 0
WalthamForest = 0
Wandsworth = 0
Westminster = 0
OuterBorough = 0
InnerBorough = 0*下面是我的当前代码和下面图像的输出：
#Start of Imports
import csv
import sys
import numpy as np
import pandas as pd
import re
import matplotlib.pyplot as plt
#End of Imports
#Start of Declarations
COL = 0
Barnet = 0
Bexley = 0
BAD = 0
Brent = 0
Bromley = 0
Camden = 0
Croydon = 0
Ealing = 0
#This is as far as I got when I thought something was wrong?
Enfield = 0
Greenwich = 0
Hackney = 0
HAF = 0
Haringey = 0
Harrow = 0
Havering = 0
Hillingdon = 0
Hounslow = 0
Islington = 0
KAC = 0
KUT = 0
Lambeth = 0
Lewisham = 0
Merton = 0
Newham = 0
Redbridge = 0
RUT = 0
Southwark = 0
Sutton = 0
TowerHamlets = 0
WalthamForest = 0
Wandsworth = 0
Westminster = 0
OuterBorough = 0
InnerBorough = 0
#End of Declarations
#Starts reading 'csv file'
csv = pd.read_csv ('land-area-population-density-london.csv') #Not sure what this does, index_col=3)
#Start of IF Statement
csva = np.array(csv)
for column in np.arange(0, csva.shape[0]):
if re.match(r"Barnet", str(csva[column][2])) is not None:
Barnet = Barnet + 1
elif re.match(r"Bexley", str(csva[column][2])) is not None:
Bexley = Bexley + 1
elif re.match(r"City of London", str(csva[column][2])) is not None:
COL = COL + 1
elif re.match(r"Barking and Dagenham", str(csva[column][2])) is not None:
BAD = BAD + 1
elif re.match(r"Brent", str(csva[column][2])) is not None:
Brent = Brent + 1
elif re.match(r"Bromley", str(csva[column][2])) is not None:
Bromley = Bromley + 1
elif re.match(r"Camden", str(csva[column][2])) is not None:
Camden = Camden + 1
elif re.match(r"Croydon", str(csva[column][2])) is not None:
Croydon = Croydon + 1
elif re.match(r"Ealing", str(csva[column][2])) is not None:
Ealing = Ealing + 1
#End of IF Statement
#Start of graph fields
#Below: Places is the labels for the placesvar
places = ('Barnet', 'Bexley', 'City of London', 'Barking and Dagenham', 'Brent', 'Bromley', 'Camden', 'Croydon', 'Ealing')
#Below: placesvar the actual 'places' pulled from CSV
placesvar = [Barnet, Bexley, COL, BAD, Brent, Bromley, Camden, Croydon, Ealing]
#Y Positioning numpy.arange (Again no idea what this does) length 'places pulled from csv'
y_pos = np.arange(len(placesvar))
#End of graph fields
#Start of Graph positions and Names
plt.bar(y_pos, placesvar, align='center')
plt.xticks(y_pos, places, rotation=60)
plt.ylabel('No. of occurance')
plt.xlabel('Locations')
plt.title('Occurance of Locations')
#plt.savefig('file.png')(Commented out for testing)
#End of Graph positions and Names
plt.show()这是我当前代码的输出。“Borough”列中缺少一些变量。图片：
我为任何明显的问题道歉，我是Python的新手。
下面是添加：print(csv.head())的输出
Codes ... Population per hectare 2011
0 E09000001 ... 23.405268
1 E05000026 ... 99.968726
2 E05000027 ... 76.304188
3 E05000028 ... 89.914330
4 E05000029 ... 29.647929
[5 rows x 10 columns]回答 1
Stack Overflow用户
回答已采纳
发布于 2018-06-04 05:49:09
我希望我答对了你的问题..。
这是你的问题的一个简化例子(我相信)：
输入数据test.csv：
Codes Borough
0 E1 A
1 E2 B
2 E1 A
3 E1 A
4 E3 C
5 E2 B
6 E1 A
7 E3 C代码：
import pandas as pd
import matplotlib.pyplot as plt
# read-in data
data = pd.read_csv('./test.csv', sep='\t') #adjust sep to your needs
# count occurences
occurrences = data.loc[:, 'Borough'].value_counts()
# plot histogram
plt.bar(occurrences.keys(), occurrences)
除了data.loc，您还可以使用data.iloc[:, 2]来选择第三列，而不是名为Borough的列。
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原文链接：
https://stackoverflow.com/questions/50670263
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