数据分析

数据分析

注意点：

1.整理数据时会有一些空缺的数据需要将其进行排除：

pos_not_nan = pos.isna()
print(pos_not_nan)　　

结果：

0      False
1      False
2      False
3      False
4      False
       ...  
453    False
454    False
455    False
456    False
457     True
True 为空

方法：

dics = {'PG':0,'SF':0,'PF':0,'SG':0,'C':0}
for i in range(len(pos)):
    if pos_not_nan[i]==False:
        dics[pos[i]] += 1
print(dics)

　2.画图时有一些不会可以查找网站:

例如：https://gallery.pyecharts.org

在网站中找到一些合适的图将其代码复制一下

再将里面的一些参数进行调整成自己用的参数

画饼图、柱状图：
1、划分出5个收入等级
2、绘制出饼图

柱状图：

from pyecharts import options as opts
from pyecharts.charts import Bar
a = ["0-2000000","2000001-4000000","4000001-6000000","6000001-8000000","8000001-10000000"]
b = [0,0,0,0,0]
sal = data['Salary']
sal_na = sal.isna()
for i in range(len(sal_na)):
    if sal_na[i] == False:
        if sal[i] > 0 and sal[i] < 2000000:
            b[0] += 1
        elif sal[i] > 2000001 and sal[i] < 4000000:
            b[1] += 1
        elif sal[i] > 4000001 and sal[i] < 6000000:
            b[2] += 1
        elif sal[i] > 6000001 and sal[i] < 8000000:
            b[3] += 1
        elif sal[i] > 8000001 and sal[i] < 10000000:
            b[4] += 1
c = (
    Bar()
    .add_xaxis(a)
    .add_yaxis("分段",b)
    .set_global_opts(
        xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),
        title_opts=opts.TitleOpts(title="Bar-旋转X轴标签", subtitle="解决标签名字过长的问题"),
    )
    .render("bar_rotate_xaxis_label.html")
)

饼图：

from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Faker
d = 0
f = 0
e = []
for i in range(len(b)):
    d += b[i]
for j in range(len(b)):
    f = round(b[j]/d*100,2)
    e.append(f)

c = (
    Pie()
    .add(
        "",
        [list(z) for z in zip(a, e)],
        center=["35%", "50%"],
    )
    .set_global_opts(
        title_opts=opts.TitleOpts(title="Pie-调整位置"),
        legend_opts=opts.LegendOpts(pos_left="15%"),
    )
    .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:({d}%)"))
    .render("pie_position.html")
)