This article has participated in the “Digitalstar Project” and won a creative gift package to challenge the creative incentive money
takeaway
Fat friends, recently a fan found me blunt offer let me do my homework, I listened to the spot on the eye. Am I such a person?
Ask him directly how much money, hee hee hee!! Of course, how much money is not dry, since it is a fan I certainly try to help ah, so I began today’s blog.
Climb the Chinese university rankings
Link: Chinese university rankings are actually quite simple, this fan certainly did not have a good look at my previous articles, this kind of climb said many times. So let’s just do it.
We directly find the ID or class of the information we want to obtain
res=requests.get(url=url,headers=header).content.decode('utf-8')
soup=BeautifulSoup(res,'lxml')
names=soup.findAll(name="a",attrs={"class":"name-cn"})
xinxi=soup.findAll("td")
with open("Chinese University. CSV".'a', encoding="utf-8", newline="") as f:
for i in range(0.len(xinxi),6):
w=csv.writer(f)
w.writerow([xinxi[i].text.strip(),xinxi[i+1].text.strip(),xinxi[i+2].text.strip(),xinxi[i+3].text.strip(),xinxi[i+4].text.strip(),xinxi[i+5].text.strip()])
Copy the codeAnd get the information
Visual analysis
The word cloud
We have got the information above. We first do a word cloud analysis on the provinces and categories where these universities are concentrated
You can see that the majority of comprehensive and Beijing
import jieba
from wordcloud import WordCloud
from matplotlib import colors
import csv
import pandas as pd
info=pd.read_csv("Chinese University. CSV",usecols=[2.3])
text=info
cut_text = "".join(jieba.cut(str(text)))
color_list=['#FF0000'.'#9955FF'.'#66FFFF']Create a color array
colormap=colors.ListedColormap(color_list)# call
#color_mask = cv2.imread("11.jpg")
word_cloud=WordCloud(
font_path="msyh.ttc",
background_color='black',
mode="RGBA",
prefer_horizontal=1.#mask=color_mask,
height=200,
width=200,
scale=1,
colormap=colormap,# set color
margin=5
)
word_cloud1=word_cloud.generate(cut_text)
word_cloud1.to_file('2.png')
print("Image saved successfully")
Copy the codeBar chart
This is done with Echarts and if you’re interested you can do it with CuffLinks and get the same effect
// Only the js variable part is posted here
option = {
title: {
text: 'University Data in China'
},
tooltip: {
trigger: 'axis'
},
legend: {
data: ['total'.'School level']},grid: {
left: '3%'.right: '4%'.bottom: '3%'.containLabel: true
},
toolbox: {
feature: {
saveAsImage: {}}}.xAxis: {
type: 'category'.boundaryGap: false.data: [1.2.3.4.5.6.7.8.9.10.11.12.13.14.15.16.17.18.19.20.21.22.23.24.25.26.27.28.29.30]},yAxis: {
type: 'value'
},
series: [{name: 'total'.type: 'line'.stack: 'Total'.data: [969.2.855.3.768.7.723.4.654.8.649.7.577.0.574.3.567.9.537.9.522.6.519.3.518.3.516.6.513.8.508.3.488.1.487.8.474.0.465.3.447.0.444.3.442.2.435.7.430.5.427.8.419.8.418.2.401.8.400.4] {},name: 'School level'.type: 'line'.stack: 'Total'.data: [37.9.36.1.34.3.35.5.35.1.36.6.40.0.32.1.31.8.34.5.32.7.30.9.34.8.30.7.32.8.33.2.34.3.34.5.32.3.31.5.28.8.32.7.30.8.30.4.32.4.32.7.30.5.30.2.35.2.31.8]]}};Copy the codeObtain the dynamic geographic coordinates of universities above 211 in China
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
plt.rcParams['animation.writer'] = 'html'
plt.rcParams['animation.embed_limit'] = 100
def rgba_to_rgb(img_rgba) :
img_rgb = Image.new("RGB", img_rgba.size, (255.255.255))
img_rgb.paste(img_rgba, mask=img_rgba.split()[3])
return img_rgb
def html_to_gif(html_file, gif_file, duration=0.5) :
path = html_file.replace(".html"."_frames")
images = [os.path.join(path, x) for x in sorted(os.listdir(path))]
frames = [imageio.imread(x) for x in images]
if frames[0].shape[-1] = =4:
frames = [np.array(rgba_to_rgb(Image.fromarray(x))) for x in frames]
imageio.mimsave(gif_file, frames, 'gif', duration=duration)
return gif_file
cmap = ['#2E91E5'.'#1CA71C'.'#DA16FF'.'#B68100'.'#EB663B'.'#00A08B'.'#FC0080'.'#6C7C32'.'#862A16'.'# 620042'.'#DA60CA'.'#0D2A63'] * 100
def getCoords(geom) :
if isinstance(geom, geo.MultiPolygon):
return [np.array(g.exterior) for g in geom.geoms]
elif isinstance(geom, geo.Polygon):
return [np.array(geom.exterior)]
elif isinstance(geom, geo.LineString):
return [np.array(geom)]
elif isinstance(geom, geo.MultiLineString):
return [np.array(x) for x in list(geom.geoms)]
else:
raise Exception("geom must be one of [polygon,MultiPolygon,LineString,MultiLineString]!")
# Base map data
dfprovince = gpd.read_file("dfprovince.geojson").set_crs("epsg:4326").to_crs("epsg:2343")
dfnanhai = gpd.read_file("dfnanhai.geojson").set_crs("epsg:4326").to_crs("epsg:2343")
dfline9 = dfnanhai[(dfnanhai["LENGTH"] > 1.0) & (dfnanhai["LENGTH"] < 2.0)]
# Scatter data
df985 = gpd.read_file("985 University of China. Geojson").set_crs("epsg:4326").to_crs("epsg:2343")
df211 = gpd.read_file("211 University of China. Geojson").set_crs("epsg:4326").to_crs("epsg:2343")
dfpoints = pd.concat([df985, df211], axis=0)
df = pd.DataFrame({"x": [pt.x for pt in dfpoints["geometry"]],
"y": [pt.y for pt in dfpoints["geometry"]]})
df["z"] = 1.0
df.index = dfpoints["name"].values
def bubble_map_dance(df, title=Location distribution of 116 211 Universities in China,
filename=None,
figsize=(8.6), dpi=144,
duration=0.5,
anotate_points=[Beijing University of Posts and Telecommunications."Nanchang University"."Huazhong Agricultural University".Donghua University.Yunnan University.Shaanxi Normal University.Inner Mongolia University."Xizang University"."Xinjiang University"."Qinghai University"."Harbin Engineering University"]) :
fig, ax_base = plt.subplots(figsize=figsize, dpi=dpi)
ax_child = fig.add_axes([0.800.0.125.0.10.0.20])
def plot_frame(i) :
ax_base.clear()
ax_child.clear()
# Draw provincial boundaries
polygons = [getCoords(x) for x in dfprovince["geometry"]]
for j, coords in enumerate(polygons):
for x in coords:
poly = plt.Polygon(x, fill=True, ec="gray", fc="white", alpha=0.5, linewidth=8.)
poly_child = plt.Polygon(x, fill=True, ec="gray", fc="white", alpha=0.5, linewidth=8.)
ax_base.add_patch(poly)
ax_child.add_patch(poly_child)
Draw a nine-dash line
coords = [getCoords(x) for x in dfline9["geometry"]]
lines = [y for x in coords for y in x]
for ln in lines:
x, y = np.transpose(ln)
line = plt.Line2D(x, y, color="gray", linestyle="-.", linewidth=1.5)
line_child = plt.Line2D(x, y, color="gray", linestyle="-.", linewidth=1.5)
ax_base.add_artist(line)
ax_child.add_artist(line_child)
Set the spine format
for spine in ['top'.'left'."bottom"."right"]:
ax_base.spines[spine].set_color("none")
ax_child.spines[spine].set_alpha(0.5)
ax_base.axis("off")
# Set the drawing range
bounds = dfprovince.total_bounds
ax_base.set_xlim(bounds[0] - (bounds[2] - bounds[0) /10, bounds[2] + (bounds[2] - bounds[0) /10)
ax_base.set_ylim(bounds[1] + (bounds[3] - bounds[1) /3.5, bounds[3] + (bounds[3] - bounds[1) /100)
ax_child.set_xlim(bounds[2] - (bounds[2] - bounds[0) /2.5, bounds[2] - (bounds[2] - bounds[0) /20)
ax_child.set_ylim(bounds[1] - (bounds[3] - bounds[1) /20, bounds[1] + (bounds[3] - bounds[1) /2)
# Remove the axis scale
ax_child.set_xticks([]);
ax_child.set_yticks([]);
k = i // 3 + 1
m = i % 3
text = "NO." + str(k)
dfdata = df.iloc[:k, :].copy()
dftmp = df.iloc[:k - 1, :].copy()
# Draw scatter image
if len(dftmp) > 0:
ax_base.scatter(dftmp["x"], dftmp["y"], s=100 * dftmp["z"] / df["z"].mean(),
c=(cmap * 100) [0:len(dftmp)], alpha=0.3, zorder=3)
ax_child.scatter(dftmp["x"], dftmp["y"], s=100 * dftmp["z"] / df["z"].mean(),
c=(cmap * 100) [0:len(dftmp)], alpha=0.3, zorder=3)
Add comment text
for i, p in enumerate(dftmp.index):
px, py, pz = dftmp.loc[p, ["x"."y"."z"]].tolist()
if p in anotate_points:
ax_base.annotate(p, xy=(px, py), xycoords="data", xytext=(-15.10),
fontsize=10, fontweight="bold", color=cmap[i], textcoords="offset points")
Add a title and rank number
# ax_base.set_title(title,color = "black",fontsize = 12)
ax_base.text(0.5.0.95, title, va="center", ha="center",
size=12, transform=ax_base.transAxes)
ax_base.text(0.5.0.5, text, va="center", ha="center",
alpha=0.3, size=50, transform=ax_base.transAxes)
# Add attention animation
if m == 0:
px, py, pz = dfdata["x"] [[...1]], dfdata["y"] [[...1]], dfdata["z"] [-1]
p = dfdata.index[-1]
ax_base.scatter(px, py, s=800 * pz / df["z"].mean(),
c=cmap[len(dfdata) - 1:len(dfdata)], alpha=0.5, zorder=4)
ax_base.annotate(p, xy=(px, py), xycoords="data",
xytext=(-15.10), fontsize=20, fontweight="bold",
color=cmap[k - 1], textcoords="offset points", zorder=5)
if m == 1:
px, py, pz = dfdata["x"] [[...1]], dfdata["y"] [[...1]], dfdata["z"] [-1]
p = dfdata.index[-1]
ax_base.scatter(px, py, s=400 * pz / df["z"].mean(),
c=cmap[len(dfdata) - 1:len(dfdata)], alpha=0.5, zorder=4)
ax_base.annotate(p, xy=(px, py), xycoords="data",
xytext=(-15.10), fontsize=15, fontweight="bold",
color=cmap[k - 1], textcoords="offset points", zorder=5)
if m == 2:
px, py, pz = dfdata["x"] [[...1]], dfdata["y"] [[...1]], dfdata["z"] [-1]
p = dfdata.index[-1]
ax_base.scatter(px, py, s=100 * pz / df["z"].mean(),
c=cmap[len(dfdata) - 1:len(dfdata)], alpha=0.5, zorder=4)
ax_base.annotate(p, xy=(px, py), xycoords="data",
xytext=(-15.10), fontsize=10, fontweight="bold",
color=cmap[k - 1], textcoords="offset points", zorder=5)
my_animation = animation.FuncAnimation(fig, plot_frame, frames=range(0.3 * len(df)), interval=int(duration * 1000))
if filename is None:
try:
from IPython.display import HTML
HTML(my_animation.to_jshtml())
return HTML(my_animation.to_jshtml())
except ImportError:
pass
else:
my_animation.save(filename)
return filename
Copy the codeFinally said to the fat friend
For the fans of this fight, I think the real charge is probably this, I haven’t written Python for a few days, this one is straight to me. Keep an eye on me for the Java and Python web. Finally or that sentence together fat learning, refueling