import pandas as pd
###根据行来求平均值
def fill_NAN():
filePath = r'E:\study-python\0819\filled_meter-500.csv'
df0 = pd.read_csv(filePath, engine='python', encoding='utf-8-sig')
df = df0.drop("MeterNo", axis=1)
df2 = df.T
#df3 = df2.fillna(df2.mean()) ##平均值
#df3 = df2.fillna(df2.median()) ##中位数
df3 = df2.fillna(method='ffill').fillna(method='bfill')##用前一个非缺失值去填充该缺失值
##用下一个非缺失值填充该缺失值
df4 = df3.T
##合并表号方法一
#df4.loc[:, "MeterNo"] = df0['MeterNo']
##合并方法2
##pandas-两个Series拼接合并为一个DataFrame(pd.concat)
df4 = pd.concat([df0['MeterNo'],df4], axis=1)
print(df4)
filePath = r'E:\study-python\0819\filled_meter-500-after.csv'
df4.to_csv(filePath, encoding='utf-8-sig') # 存下该数据
if __name__ == '__main__':
fill_NAN()