建立 pandas
- import pandas as pd
- import numpy as np
- p=pd.Series(range(1,12))#Series 大写
- print(p)
- p=pd.Series(np.random.rand(4))
- print(p)
- p=pd.Series({
- "A":1,"B":32
- })
- print(p)
- p=pd.Series(np.random.rand(4),index=["a","b","c","d"])
- print(p)
数据预览
- p=pd.Series(np.random.rand(4),index=["a","b","c","d"])
- print(p.head(2))
- print(p.tail(2))
数据索引
- import pandas as pd
- import numpy as np
- p=pd.Series(np.random.rand(400))
- print(p.head(2))
- print(p.tail(2))
- print(p.index)
- print(p.name)
- print(p.index.name)
- p.index.name="index"
- p.name="p_num"
- print(p)
位置
- import pandas as pd
- import numpy as np
- p=pd.Series(np.random.rand(5))
- print(p)
- print(p[2])
- print(p.loc[2])
- print(p.iloc[2])# 当索引为数字的时候, 三者一样
构建 dataframe
- import pandas as pd
- import numpy as np
- a=np.ceil(np.random.rand(71,4)*149)
- df=pd.DataFrame(a)
- print(df.head(4))
- df.index# 行名
- df.columns# 列名
改行名字和索引
- import pandas as pd
- import numpy as np
- a=np.ceil(np.random.rand(71,4)*149)
- df=pd.DataFrame(a)
- df.columns=["a","b","c","d"]# 改行名字
- a=df.columns
- df=df.drop(columns=["c","d"])# 丢弃 cd 列
- df["E"]=np.ceil(np.random.rand(71,1)*149)# 增加一列
- print(df["a"])# 按名字取行
- print(df.head(4))
重置 index
- import pandas as pd
- import numpy as np
- a=np.ceil(np.random.rand(71,4)*149)
- df=pd.DataFrame(a)
- df.columns=["a","b","c","d"]# 改行名字
- a=df.columns
- df=df.drop(columns=["c","d"])# 丢弃 cd 列
- df["E"]=np.ceil(np.random.rand(71,1)*149)# 增加一列
- print(df["a"])# 按名字取行
- print(df.head(4))
- print(df[32:52])# 取行, 用逗号不行
- d=df[32:45]
- print(d)
- d=d.reset_index()# 重置 index
- print(d)
dataframe 索引
- import pandas as pd
- import numpy as np
- c1=pd.Series({
- "name":"china","language":"c","AREA":12321
- })
- c3=pd.Series({
- "name":"america","AREA":18321,"language":"e"
- })
- c2=pd.Series({
- "name":"japan","AREA":191,"language":"j"
- })
- df=pd.DataFrame([c1,c2,c3],index=["c","a","j"])
- print(df)
- print(df["AREA"])# 取列
- print(df[["AREA","language"]])# 取多列
- print(df.loc["c"])# 行名字取行
- print(df.iloc[0])# 行索引取行
- print(df.iloc[0]["language"])# 混合索引
- print(df.loc["c"]["language"])# 混合索引
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