Merge branch 'master' of https://github.com/JustDoPython/python-examples

Author: cxhuan

chaoxi/BaseMap/Python_BaseMap1.py

@@ -0,0 +1,96 @@
+import matplotlib.pyplot as plt
+from mpl_toolkits.basemap import Basemap
+import numpy as np
+
+# 画海岸线
+def drawcoast():
+
+    plt.figure(figsize=(12, 8))
+    m = Basemap()   # 创建一个地图
+    m.drawcoastlines()   # 画海岸线
+    plt.show()   # 显示图像
+
+# 地球基本画法
+def draw_basic():
+    map = Basemap(projection='ortho', lat_0=0, lon_0=0)
+    map.drawmapboundary(fill_color='aqua')
+    map.fillcontinents(color='gray',lake_color='aqua')
+    map.drawcoastlines()
+    plt.show()
+
+# 画中国地图
+def draw_china():
+    plt.figure(figsize=(10, 6))
+    m = Basemap(llcrnrlon=77, llcrnrlat=14, urcrnrlon=140, urcrnrlat=51, projection='lcc', lat_1=33, lat_2=45,
+                lon_0=100)
+    m.drawcountries(linewidth=1.5)
+    m.drawcoastlines()
+    plt.show()
+
+# 画地球人口分布图
+def drawearth():
+    names = []
+    pops = []
+    lats = []
+    lons = []
+    countries = []
+    file = open("data/main_city", encoding='utf-8').readlines()
+    for line in file:
+        info = line.split()
+        names.append(info[0])
+        pops.append(float(info[1]))
+        lat = float(info[2][:-1])
+        if info[2][-1] == 'S': lat = -lat
+        lats.append(lat)
+        lon = float(info[3][:-1])
+        if info[3][-1] == 'W': lon = -lon + 360.0
+        lons.append(lon)
+        country = info[4]
+        countries.append(country)
+    # set up map projection with
+    # use low resolution coastlines.
+    map = Basemap(projection='ortho', lat_0=35, lon_0=120, resolution='l')
+    # draw coastlines, country boundaries, fill continents.
+    map.drawcoastlines(linewidth=0.25)
+    map.drawcountries(linewidth=0.25)
+    # draw the edge of the map projection region (the projection limb)
+    map.drawmapboundary(fill_color='#689CD2')
+    # draw lat/lon grid lines every 30 degrees.
+    map.drawmeridians(np.arange(0, 360, 30))
+    map.drawparallels(np.arange(-90, 90, 30))
+    # Fill continent wit a different color
+    map.fillcontinents(color='#BF9E30', lake_color='#689CD2', zorder=0)
+    # compute native map projection coordinates of lat/lon grid.
+    x, y = map(lons, lats)
+    max_pop = max(pops)
+    # Plot each city in a loop.
+    # Set some parameters
+    size_factor = 80.0
+    y_offset = 15.0
+    rotation = 30
+    for i, j, k, name in zip(x, y, pops, names):
+        size = size_factor * k / max_pop
+        cs = map.scatter(i, j, s=size, marker='o', color='#FF5600')
+        plt.text(i, j + y_offset, name, rotation=rotation, fontsize=10)
+
+    plt.title('earth')
+    plt.show()
+
+# 画带投影的地球图片
+def draw_earth1():
+    import matplotlib.pyplot as plt
+    from mpl_toolkits.basemap import Basemap
+    plt.figure(figsize=(8, 8))
+    # 正射投影，投影原点设在了上海周边
+    m = Basemap(projection='ortho', resolution=None, lat_0=30, lon_0=120)
+    # 图像原始分辨率是5400*2700，设置scale = 0.5以后分辨率为2700*1350,如此作图
+    # 迅速不少也不那么占用内存了
+    m.bluemarble(scale=0.5)
+    plt.show()
+
+if __name__ == '__main__':
+    #drawcoast()
+    drawearth()
+    #draw_basic()
+    #draw_china()
+    #draw_earth1()

chaoxi/BaseMap/main_city

@@ -0,0 +1,9 @@
+Shanghai 23019148  31.23N  121.47E  China
+Mumbai   12478447  18.96N  72.82E   India
+Karachi  13050000  24.86N  67.01E   Pakistan
+Delhi    16314838  28.67N  77.21E   India
+Manila   11855975  14.62N  120.97E  Philippines
+Seoul    23616000  37.56N  126.99E  Korea(South)
+Jakarta  28019545   6.18S  106.83E  Indonesia
+Tokyo    35682460  35.67N  139.77E  Japan
+Peking   19612368  39.91N  116.39E  China

chaoxi/Pandas1/pandas_example.py

@@ -0,0 +1,47 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+def craw_bar():
+    df2 = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
+    df2.plot.bar()
+    plt.show()
+
+def craw_line():
+    ts = pd.Series(np.random.randn(1000), index=pd.date_range("1/1/2000", periods=1000))
+    ts = ts.cumsum()
+    ts.plot()
+    plt.show()
+
+def craw_line1():
+    ts = pd.Series(np.random.randn(1000), index=pd.date_range("1/1/2000", periods=1000))
+    df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=list("ABCD"))
+    df = df.cumsum()
+    df.plot()
+    plt.show()
+
+
+def craw_bar():
+    ts = pd.Series(np.random.randn(1000), index=pd.date_range("1/1/2000", periods=1000))
+    df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=list("ABCD"))
+    plt.figure()
+    df.iloc[5].plot(kind="bar")
+    plt.show()
+
+def craw_bar1():
+    df2 = pd.DataFrame(np.random.rand(10, 4), columns=["a", "b", "c", "d"])
+    df2.plot.bar()
+    plt.show()
+
+def craw_bar2():
+    df2 = pd.DataFrame(np.random.rand(10, 4), columns=["a", "b", "c", "d"])
+    df2.plot.bar(stacked=True)
+    plt.show()
+
+def craw_bar3():
+    df2 = pd.DataFrame(np.random.rand(10, 4), columns=["a", "b", "c", "d"])
+    df2.plot.barh(stacked=True)
+    plt.show()
+
+if __name__ == '__main__':
+    craw_bar3()

chaoxi/Pandas2/pandas_example1.py

@@ -0,0 +1,45 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+def draw_pie():
+
+    series = pd.Series(3 * np.random.rand(4), index=["1", "2", "3", "4"], name="series")
+    series.plot.pie(figsize=(6, 6));
+    plt.show()
+
+
+def draw_pie1():
+    df = pd.DataFrame(
+        3 * np.random.rand(4, 2), index=["a", "b", "c", "d"], columns=["x", "y"])
+    df.plot.pie(subplots=True, figsize=(8, 4), legend=False)
+    plt.show()
+
+def draw_pie2():
+    series = pd.Series(3 * np.random.rand(4), index=["1", "2", "3", "4"], name="series")
+    series.plot.pie(
+        labels=["A", "B", "C", "D"],
+        colors=["r", "g", "b", "c"],
+        autopct="%.2f",
+        fontsize=20,
+        figsize=(6, 6),)
+    plt.show()
+
+def draw_pie3():
+    series = pd.Series([0.1] * 4, index=["a", "b", "c", "d"], name="series2")
+    series.plot.pie(figsize=(6, 6))
+    plt.show()
+
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from pandas.plotting import scatter_matrix
+def draw_pie4():
+
+    df = pd.DataFrame(np.random.randn(1000, 4), columns=["a", "b", "c", "d"])
+
+    scatter_matrix(df, alpha=0.2, figsize=(6, 6), diagonal="kde")
+    plt.show()
+
+if __name__ == '__main__':
+    draw_pie4()

chaoxi/README.md

@@ -7,7 +7,13 @@ Python技术 公众号文章代码库
 
 ![](http://favorites.ren/assets/images/python.jpg)
 
-## 实例代码
+## 实例代码 
+
+[神器 Pandas 绘图大全(上)！](https://github.com/JustDoPython/python-examples/tree/master/chaoxi/Pandas2) 神器 Pandas 绘图大全(中)！
+
+[神器 Pandas 绘图大全(上)！](https://github.com/JustDoPython/python-examples/tree/master/chaoxi/Pandas1) 神器 Pandas 绘图大全(上)！
+
+[神器-可视化分析之Basemap实战详解（二）](https://github.com/JustDoPython/python-examples/tree/master/chaoxi/BaseMap) 神器-可视化分析之Basemap实战详解（二）
 
 [用 Python 给小表弟画皮卡丘！](https://github.com/JustDoPython/python-examples/tree/master/chaoxi/pkq) 用 Python 给小表弟画皮卡丘！
 

moumoubaimifan/README.md

@@ -10,6 +10,8 @@ Python技术 公众号文章代码库
 
 ## 实例代码
 
+[又是入刑的一天！抓取 jk 小姐姐图片](https://github.com/JustDoPython/python-examples/tree/master/moumoubaimifan/jk)
+
 [我不做韭菜！用 python 分析基金中的股票信息](https://github.com/JustDoPython/python-examples/tree/master/moumoubaimifan/stock.py)
 
 [python 抓取阿里云盘资源](https://github.com/JustDoPython/python-examples/tree/master/moumoubaimifan/aliso)

moumoubaimifan/jk/jk.py

@@ -0,0 +1,60 @@
+import requests
+import time
+import json
+import re
+
+header = {
+    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36'
+}
+
+def get_list():
+
+    try:
+        url = 'https://bcy.net/apiv3/common/circleFeed?circle_id=492&since='+str(int(time.time()))+'.000000&sort_type=2&grid_type=10'
+        response = requests.get(url,headers= header)
+        response.raise_for_status()
+        #转码
+        response.encoding = 'utf-8'
+        return response.text
+    except:                     
+        print("Failed!")                                                                                            
+
+def parse_list(data):
+    item_ids = []
+    json_data = json.loads(data)
+    for item in json_data['data']['items']:
+        item_ids.append(item['item_detail']['item_id'])
+    return item_ids
+
+def get_item(item_ids):
+    intercepts = []
+    for id in item_ids:
+        url = 'https://bcy.net/item/detail/'+ str(id) + '?_source_page=hashtag'
+        response = requests.get(url, headers = header)
+        response.encoding = 'utf-8'
+        text = response.text
+        intercept = text[text.index('JSON.parse("') + len('JSON.parse("'): text.index('");')].replace(r'\"',r'"')
+        intercepts.append(intercept)
+    return intercepts
+    
+def download(intercepts):
+    for i in intercepts:
+        # json_data = json.loads(i)
+        pattern = re.compile('"multi":\[{"path":"(.*?)","type"')
+        pattern_item_id = re.compile('"post_data":{"item_id":"(.*?)","uid"')
+        b = pattern.findall(i)
+        item_id  = pattern_item_id.findall(i)[0]
+        index = 0
+        for url in b:
+            index = index + 1
+            content = re.sub(r'(\\u[a-zA-Z0-9]{4})',lambda x:x.group(1).encode("utf-8").decode("unicode-escape"),url)
+            response = requests.get(content.replace('\\',''))
+            with open('D:\\bcy\\' + str(item_id) + str(index) + '.png', 'wb') as f:
+                f.write(response.content)
+
+if __name__ == '__main__':
+    data = get_list()
+    item_ids = parse_list(data)
+    intercepts = get_item(item_ids)
+    download(intercepts)
+