随笔分类 - python_pandas
摘要：///////////////////////////////////////////////// df = pd.DataFrame({"ID":[1,2,3], "Name":["Time", "Victor", "Nick"]}) df = df.set_index("ID") # 设置索引
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摘要：import pandas as pd import matplotlib.pyplot as plt from scipy.stats import linregress if __name__ == '__main__': pd.options.display.max_columns = 999
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摘要：import pandas as pd if __name__ == '__main__': page_1 = pd.read_excel("C:/Users/18124/Desktop/pandas/027_行操作/Students.xlsx", sheet_name="Page_001") pa
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摘要：import pandas as pd import pyodbc import sqlalchemy if __name__ == '__main__': # 方法一 connection = pyodbc.connect("driver={sql server}; server=(local);
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摘要：import pandas as pd if __name__ == '__main__': pd.options.display.max_columns = 999 Videos = pd.read_excel("C:/Users/18124/Desktop/pandas/021_旋转数据表/Vi
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摘要：import pandas as pd import numpy as np if __name__ == '__main__': pd.options.display.max_columns = 999 orders = pd.read_excel("C:/Users/18124/Desktop/
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摘要：import pandas as pd if __name__ == '__main__': student = pd.read_excel("C:/Users/18124/Desktop/pandas/019_求和_求平均_统计引导/Students.xlsx", \ engine="openpy
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摘要：import pandas as pd # 校验函数 : 校验数据; 校验数据关系 # 校验结果 : run; excel def score_validation(row): # 方法一 try: assert 0 <= row.Score <= 100 except: print(f"#{row
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摘要：''' 散点图: 1 下图房屋面积(sqft_basement)与价格关系(price) 直方图: 1 下图房子集中在什么价位 2 下图面积集中在什么面积 密度图: 1 下图房子多大概率70w ''' import pandas as pd import matplotlib.pyplot as p
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摘要：import pandas as pd import matplotlib.pyplot as plt if __name__ == '__main__': weeks = pd.read_excel("C:/Users/123/Desktop/pandas/013_折线趋势图_叠加区域图/Orde
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摘要：import pandas as pd import matplotlib.pyplot as plt if __name__ == '__main__': student = pd.read_excel("C:/Users/123/Desktop/pandas/012_饼图/Students.xl
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摘要：import pandas as pd import matplotlib.pyplot as plt if __name__ == '__main__': students = pd.read_excel("C:/Users/123/Desktop/pandas/010_叠加柱状图_水平柱状图/S
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摘要：import pandas as pd import numpy as np def get_circumcircle_area(l, h): r = np.sqrt(l**2 + h**2) / 2 return r**2 * np.pi def warapper(row): result = g
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摘要：import pandas as pd import numpy as np if __name__ == '__main__': page_1 = pd.read_excel("C:/Users/18124/Desktop/pandas/027_行操作/Students.xlsx", sheet_
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摘要：import pandas as pd import seaborn as sns # 表示数值大小 - 背景颜色深浅 color_map = sns.light_palette("green", as_cmap=True) students = pd.read_excel("C:/Users/18
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摘要：import pandas as pd # 标记 - 不及格 def low_score_read(s): if s < 60: color = "red" else: color = "black" return f"color:{color}" # 标记 - 最高分 def highest_sc
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摘要：import pandas as pd if __name__ == '__main__': # 读取文件 : csv - , student_s1 = pd.read_csv("C:/Users/18124/Desktop/pandas/022_读取CSV_TSV_TXT文件中的数据/Studen
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摘要：import pandas as pd if __name__ == '__main__': student = pd.read_excel("C:/Users/18124/Desktop/pandas/020_定位_消除重复数据/副本Students_Duplicates.xlsx", \ eng
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摘要：import pandas as pd if __name__ == '__main__': employees = pd.read_excel("C:/Users/18124/Desktop/pandas/018_一列数据分割两列/Employees.xlsx") print(employees)
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摘要：import pandas as pd if __name__ == '__main__': pd.options.display.max_columns = 777 students = pd.read_excel("C:/Users/123/Desktop/pandas/016_多表联合/Stu
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