tft每日頭條

 > 科技

 > python讀取csv文件

python讀取csv文件

科技 更新时间:2025-01-25 11:12:39

'''要在文本文件中存儲數據,最簡單的方式是将數據作為一系列以逗号分隔的值(CSV)寫入文件數據來源:sitka_weather_07-2014.csv'''

分析csv文件頭

import csv filename = 'sitka_weather_07-2014.csv' with open(filename) as f: reader = csv.reader(f)#打開文件,并存儲在列表中 header_row = next(reader)#返回文件的下一行 print(header_row) ['AKDT', 'Max TemperatureF', 'Mean TemperatureF', 'Min TemperatureF', 'Max Dew PointF', 'MeanDew PointF', 'Min DewpointF', 'Max Humidity', ' Mean Humidity', ' Min Humidity', ' Max Sea Level PressureIn', ' Mean Sea Level PressureIn', ' Min Sea Level PressureIn', ' Max VisibilityMiles', ' Mean VisibilityMiles', ' Min VisibilityMiles', ' Max Wind SpeedMPH', ' Mean Wind SpeedMPH', ' Max Gust SpeedMPH', 'PrecipitationIn', ' CloudCover', ' Events', ' WindDirDegrees']

打印文件頭及其位置

for index,column_header in enumerate(header_row):#enumerate獲取每個元素的索引及值 print(index,column_header) 0 AKDT 1 Max TemperatureF 2 Mean TemperatureF 3 Min TemperatureF 4 Max Dew PointF 5 MeanDew PointF 6 Min DewpointF 7 Max Humidity 8 Mean Humidity 9 Min Humidity 10 Max Sea Level PressureIn 11 Mean Sea Level PressureIn 12 Min Sea Level PressureIn 13 Max VisibilityMiles 14 Mean VisibilityMiles 15 Min VisibilityMiles 16 Max Wind SpeedMPH 17 Mean Wind SpeedMPH 18 Max Gust SpeedMPH 19 PrecipitationIn 20 CloudCover 21 Events 22 WindDirDegrees

提取并讀取數據并繪制氣溫圖表

#讀取每天的最高氣溫 highs = [] for row in reader: #使用int将字符串轉為數字,讓matplotlib能夠讀取 high = int(row[1]) highs.append(high) print(highs) [64, 71, 64, 59, 69, 62, 61, 55, 57, 61, 57, 59, 57, 61, 64, 61, 59, 63, 60, 57, 69, 63, 62, 59, 57, 57, 61, 59, 61, 61, 66] #繪制氣溫圖表 import matplotlib.pyplot as plt fig = plt.figure(dpi = 128, figsize = (10,6)) plt.plot(highs, c = 'red') plt.title('daily high temperates, july 2014',fontsize = 24) plt.xlabel('', fontsize = 16) plt.xlabel('temperates', fontsize = 16) plt.tick_params(axis = 'both', which = 'major', labelsize = 16) plt.show()

python讀取csv文件(python數據可視化--CSV文件格式)1

image.png

在圖表中添加日期

import csv filename = 'sitka_weather_07-2014.csv' with open(filename) as f: reader = csv.reader(f)#打開文件,并存儲在列表中 header_row = next(reader)#返回文件的下一行 print(header_row) ###打印文件頭及其位置 for index,column_header in enumerate(header_row):#enumerate獲取每個元素的索引及值 print(index,column_header) ###提取并讀取數據 #讀取每天的最高氣溫,以及讀取圖表中日期 from datetime import datetime dates, highs = [],[] for row in reader: #使用int将字符串轉為數字,讓matplotlib能夠讀取 high = int(row[1]) highs.append(high) date = datetime.strptime(row[0], "%Y-%m-%d") dates.append(date) print(highs) #繪制氣溫圖表 import matplotlib.pyplot as plt fig = plt.figure(dpi = 128, figsize = (10,6)) plt.plot(dates, highs, c = 'red') plt.title('daily high temperates, july 2014',fontsize = 24) plt.xlabel('', fontsize = 16) fig.autofmt_xdate()#繪制斜的日期标簽 plt.ylabel('temperates', fontsize = 16) plt.tick_params(axis = 'both', which = 'major', labelsize = 16) plt.show()

python讀取csv文件(python數據可視化--CSV文件格式)2

image.png

再繪制一個數據,給圖表區域着色

import csv filename = 'sitka_weather_07-2014.csv' with open(filename) as f: reader = csv.reader(f)#打開文件,并存儲在列表中 header_row = next(reader)#返回文件的下一行 ###提取并讀取數據 #讀取每天的最高氣溫,以及讀取圖表中日期 from datetime import datetime dates, highs, lows = [],[],[] for row in reader: #使用int将字符串轉為數字,讓matplotlib能夠讀取 high = int(row[1]) highs.append(high) low = int(row[3]) lows.append(low) date = datetime.strptime(row[0], "%Y-%m-%d") dates.append(date) #繪制氣溫圖表 import matplotlib.pyplot as plt fig = plt.figure(dpi = 128, figsize = (10,6)) plt.plot(dates, highs, c = 'red', alpha = 0.5) plt.plot(dates, lows, c = 'blue', alpha = 0.5) plt.title('daily high temperates, july 2014',fontsize = 24) plt.xlabel('', fontsize = 16) fig.autofmt_xdate()#繪制斜的日期标簽 plt.ylabel('temperates', fontsize = 16) plt.fill_between(dates, highs, lows, facecolor = 'blue', alpha = 0.1)#fill_between填充顔色 plt.tick_params(axis = 'both', which = 'major', labelsize = 16) plt.show()

python讀取csv文件(python數據可視化--CSV文件格式)3

,

更多精彩资讯请关注tft每日頭條,我们将持续为您更新最新资讯!

查看全部

相关科技资讯推荐

热门科技资讯推荐

网友关注

Copyright 2023-2025 - www.tftnews.com All Rights Reserved