将数据框的特定列移动到第一列答案

【问题标题】：Moving a specific column of a dataframe to first column将数据框的特定列移动到第一列
【发布时间】：2022-11-29 12:02:58
【问题描述】：

我有一个数据框如下：

s = df.head().to_dict()
print(s)

{'BoP transfers': {1998: 12.346282212735618,
  1999: 19.06438060024298,
  2000: 18.24888031473687,
  2001: 24.860019912667006,
  2002: 32.38242225822908},
 'Current balance': {1998: -6.7953,
  1999: -2.9895,
  2000: -3.9694,
  2001: 1.1716,
  2002: 5.7433},
 'Domestic demand': {1998: 106.8610389799729,
  1999: 104.70302507466538,
  2000: 104.59254229534136,
  2001: 103.83532232336977,
  2002: 102.81709401489702},
 'Effective exchange rate': {1998: 88.134,
  1999: 95.6425,
  2000: 99.927725,
  2001: 101.92745,
  2002: 107.85565},
 'RoR (foreign liabilities)': {1998: 0.0433,
  1999: 0.0437,
  2000: 0.0542,
  2001: 0.0539,
  2002: 0.0474},
 'Gross foreign assets': {1998: 19.720897432405103,
  1999: 22.66200738564236,
  2000: 25.18270679890144,
  2001: 30.394226651732836,
  2002: 37.26477320359688},
 'Gross domestic income': {1998: 104.9037939043707,
  1999: 103.15361867816479,
  2000: 103.06777792080423,
  2001: 102.85886528974339,
  2002: 102.28518242008846},
 'Gross foreign liabilities': {1998: 60.59784839338306,
  1999: 61.03308220978983,
  2000: 64.01438055825233,
  2001: 67.07798172469921,
  2002: 70.16108592109364},
 'Inflation rate': {1998: 52.6613,
  1999: 19.3349,
  2000: 16.0798,
  2001: 15.076,
  2002: 17.236},
 'Credit': {1998: 0.20269913592846378,
  1999: 0.2154280880177353,
  2000: 0.282948948505006,
  2001: 0.3954812893893278,
  2002: 0.3578263032373988}}

可以使用以下方法将其转换回其原始形式：

df = pd.DataFrame.from_dict(s)

假设，我想将名为“外债总额”的列移到第一列。我知道这可以通过重建索引来完成。但是，在我的例子中，数据框有 100 列。我怎样才能在一开始就说一个特定的专栏？我阅读了 pandas pop() 方法，但在我的框架中出现错误。

【问题讨论】：

这回答了你的问题了吗？ Move column by name to front of table in pandas

标签： python pandas columnsorting

【解决方案1】：

以下是我的几种方法：

columns = df.columns.tolist()
columns.insert(0, columns.pop(columns.index("Gross foreign liabilities")))
df = df.reindex(columns=columns)

或者

col = ["Gross foreign liabilities"]
df = df[col + [x for x in df.columns if x not in col]]

【讨论】：

【解决方案2】：

你可以使用pop和insert：

name = 'Gross foreign liabilities'
df.insert(0, name, df.pop(name))

输出：

      Gross foreign liabilities  BoP transfers  Current balance  
1998                  60.597848      12.346282          -6.7953   
1999                  61.033082      19.064381          -2.9895   
2000                  64.014381      18.248880          -3.9694   
2001                  67.077982      24.860020           1.1716   
2002                  70.161086      32.382422           5.7433   

      Domestic demand  Effective exchange rate  RoR (foreign liabilities)  
1998       106.861039                88.134000                     0.0433   
1999       104.703025                95.642500                     0.0437   
2000       104.592542                99.927725                     0.0542   
2001       103.835322               101.927450                     0.0539   
2002       102.817094               107.855650                     0.0474   

      Gross foreign assets  Gross domestic income  Inflation rate    Credit  
1998             19.720897             104.903794         52.6613  0.202699  
1999             22.662007             103.153619         19.3349  0.215428  
2000             25.182707             103.067778         16.0798  0.282949  
2001             30.394227             102.858865         15.0760  0.395481  
2002             37.264773             102.285182         17.2360  0.357826

【讨论】：