readme.md

• 根据index和head赋值

df.loc['0','A'] = 1

• 合并两个df

np.concatenate((x,y),axis=0)

• 判断是否nan

if row['xxx'] is np.nan:

• 获取某列值等于某个值的行

df[df['列名'].isin([相应的值])]

• 重新从0开始索引

df.reset_index(drop=True)  

• 去掉重复值

df['xx'].drop_duplicates()

• 排序

df = df.sort_values(["xx"])

• 遍历行

for index, row in df.iterrows():
    print(row["c1"], row["c2"])
    
    
for row in df.itertuples(index=True, name='Pandas'):
    print(getattr(row, "c1"), getattr(row, "c2"))
#itertuples()应该比iterrows()快