如何以特定样式显示数据框列表？答案

【问题标题】：How to display a list of dataframes in a specific style?如何以特定样式显示数据框列表？
【发布时间】：2020-10-07 09:08:58
【问题描述】：

我已经清理了我的数据集并在不同的数据帧中分离了代码块。这些数据框被放在一个列表中。单独来说，它工作正常，但在循环中，我没有得到任何输出。

def trialflag(x):
  default=''
  green='background-color: green'
  blue='background-color: blue'
  yellow='background-color: yellow'
  orange='background-color: orange'
  red='background-color: red'
  g= x['THI Flag'] == "Green"
  b= x['THI Flag'] == "Blue"
  y= x['THI Flag'] == "Yellow"
  o= x['THI Flag'] == "Orange"
  r= x['THI Flag'] == "Red"
  df1 = pd.DataFrame(default, index=x.index, columns=x.columns)
  df1.loc[g, ['THI','THI Flag']] = green
  df1.loc[b,['THI','THI Flag']]= blue
  df1.loc[y, ['THI','THI Flag']] = yellow
  df1.loc[o,['THI','THI Flag']] = orange
  df1.loc[r,['THI','THI Flag']] = red
  return df1

for i in range(0,ntrans):
  (transformerlist[I].head(5))[['Meter_Serial_Number','THI','THI Flag','THI Action']].style.apply(trialflag,axis=None)

输出：（我什么也没得到）

对于这个例子：

def trialflag(x):
  default=''
  green='background-color: green'
  blue='background-color: blue'
  yellow='background-color: yellow'
  orange='background-color: orange'
  red='background-color: red'
  g= x['THI Flag'] == "Green"
  b= x['THI Flag'] == "Blue"
  y= x['THI Flag'] == "Yellow"
  o= x['THI Flag'] == "Orange"
  r= x['THI Flag'] == "Red"
  df1 = pd.DataFrame(default, index=x.index, columns=x.columns)
  df1.loc[g, ['THI','THI Flag']] = green
  df1.loc[b,['THI','THI Flag']]= blue
  df1.loc[y, ['THI','THI Flag']] = yellow
  df1.loc[o,['THI','THI Flag']] = orange
  df1.loc[r,['THI','THI Flag']] = red
  return df1

transdup=transformerlist[0]
transformerlist[0].head(5)[['Meter_Serial_Number','THI','THI Flag']].style.apply(trialflag,axis=None)

输出： Click to see image

我正在尝试获得一个输出，它显示了transformerlist 中每个数据帧的样式。任何想法和建议将不胜感激！

【问题讨论】：

在您的循环中，您正在调用transformerlist[I]...，但您使用i 定义您的for 循环

标签： python pandas dataframe google-colaboratory

【解决方案1】：

你需要在循环中调用display。

for df in df_list:
    df = df.style.apply(trialflag,axis=None)
    display(df)

【讨论】：