- 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