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)