003_行_列_单元格

d = {"x":100, "y":200, "z":300}
s1 = pd.Series(d)
print(s1)
print(s1.index)
print(s1.values)
# ? x行y列

########################################
L1 = [100, 200, 300]
L2 = [1000, 2000, 3000]
L3 = ["x", "y", "z"]
s2 = pd.Series(L1,  index=L3)
print(s2)


########################################
s3 = pd.Series([1000, 2000, 3000],  index=["x", "y", "z"])
print(s3)


########################################

import pandas as pd

# 列插入法
s1 = pd.Series([10, 20, 30],  index=[1, 2, 3], name="A")
s2 = pd.Series([100, 200, 300],  index=[1, 2, 3], name="B")
s3 = pd.Series([1000, 2000, 3000],  index=[1, 2, 4], name="C")

df = pd.DataFrame({s1.name:s1, s2.name:s2, s3.name:s3})
print(df)
print(df.index)
print(df.values)


# 行插入法
s1 = pd.Series([10, 100, 1000],  index=[1, 2, 3], name="A")
s2 = pd.Series([20, 200, 2000],  index=[1, 2, 3], name="B")
s3 = pd.Series([30, 300, 3000],  index=[1, 2, 3], name="C")

# 行插入法
# s1 = pd.Series([10, 100, 1000], index=["A", "B", "C"], name=1)
# s2 = pd.Series([20, 200, 2000], index=["A", "B", "C"], name=2)
# s3 = pd.Series([30, 300, 3000], index=["A", "B", "C"], name=3)

# 行插入法
# stu_add_v1 = pd.Series([41, "Student_041", 88], index=["ID", "Name", "Score"])
# stu_add_v2 = pd.Series({"ID":41, "Name":"test_name", "Score":98})
    
    
df_v2 = pd.DataFrame([s1, s2, s3])
print(df_v2)
print(df_v2.index)
print(df_v2.values)