基础练习 （1）根据列表["Python","C","Scala","Java","GO","Scala","SQL","PHP","Python"]创建一个变量名为language的Series； （2）创建一个由随机整型组成的Series，要求长度与language相同，变量名为score； （3）根据language和score创建一个DataFrame； （4）输出该DataFrame的前4行数据； （5）输出该DataFrame中language字段为Python的行； （6）将DataFrame按照score字段的值进行升序排序； （7）统计language字段中每种编程语言出现的次数。

import pandas as pd
import numpy as np

# (1) 创建Series
language = pd.Series(["Python", "C", "Scala", "Java", "GO", "Scala", "SQL", "PHP", "Python"], name="language")

# (2) 创建随机整型Series
score = pd.Series(np.random.randint(60, 101, len(language)), name="score")

# (3) 创建DataFrame
df = pd.DataFrame({"language": language, "score": score})

# (4) 输出前4行数据
print(df.head(4))

# (5) 输出language字段为Python的行
print(df[df["language"]=="Python"])

# (6) 按照score字段升序排序
df = df.sort_values(by="score")

# (7) 统计每种编程语言出现的次数
print(df["language"].value_counts())

输出结果：

  language  score
0   Python     94
1        C     69
2    Scala     79
3     Java     98
     language  score
0      Python     94
8      Python     68
6         SQL     80
10    Python      81
11      Scala     74
5       Scala     93
12       Java     60
9         PHP     77
2       Scala     79
3        Java     98
4          GO     69
1           C     69
 Python    3
 Scala     2
 Java      1
 SQL       1
 PHP       1
 C         1
 GO        1
Name: language, dtype: int64