如何隐藏Pandas DataFrame的索引列？需移除date索引列

有两种简单方式可以解决你的问题，避免date作为首列出现在结果中：

方法1：赋值完成后重置索引 #

当所有股票数据都赋值到heat_ds后，执行重置索引并丢弃原索引的操作：

heat_ds = pd.DataFrame(columns=['PFE','GS','BA','NKE','V','AAPL','TSLA','NVDA','MRK','CVX','UNH'])

heat_ds['PFE'] = pfizer['Close']
heat_ds['GS'] = goldmans['Close']
heat_ds['BA'] = boeingc['Close']
heat_ds['NKE'] = nike['Close']
heat_ds['V'] = visa['Close']
heat_ds['AAPL'] = aaple['Close']
heat_ds['TSLA'] = tesla['Close']
# 注意：你这里NVDA和MRK都用了tesla的数据，属于笔误，建议改成对应股票的Close列
heat_ds['NVDA'] = nvda['Close']
heat_ds['MRK'] = mrk['Close']
heat_ds['CVX'] = chevronc['Close']
heat_ds['UNH'] = unitedh['Close']

# 重置索引并丢弃原date索引
heat_ds = heat_ds.reset_index(drop=True)

reset_index(drop=True)会直接丢弃原来的date索引，不会将其转为普通列，同时生成默认的整数索引。

方法2：赋值时只取数值（不带索引） #

在给heat_ds的列赋值时，直接提取Series的数值部分，这样heat_ds会自动使用默认整数索引，不会继承原数据的date索引：

heat_ds = pd.DataFrame(columns=['PFE','GS','BA','NKE','V','AAPL','TSLA','NVDA','MRK','CVX','UNH'])

heat_ds['PFE'] = pfizer['Close'].values
heat_ds['GS'] = goldmans['Close'].values
heat_ds['BA'] = boeingc['Close'].values
heat_ds['NKE'] = nike['Close'].values
heat_ds['V'] = visa['Close'].values
heat_ds['AAPL'] = aaple['Close'].values
heat_ds['TSLA'] = tesla['Close'].values
heat_ds['NVDA'] = nvda['Close'].values
heat_ds['MRK'] = mrk['Close'].values
heat_ds['CVX'] = chevronc['Close'].values
heat_ds['UNH'] = unitedh['Close'].values

.values会返回Series的numpy数组形式，赋值后不会带入原索引信息。

另外提醒：你代码里NVDA和MRK的取值都用了tesla['Close']，这是明显的复制粘贴笔误，记得改成对应股票的Close数据列，否则这两列的数据会和TSLA完全一致。

内容的提问来源于stack exchange，提问作者jomjac