熊貓散點圖中的錯誤

Question

我試圖想像Galton Height Data。我已經複製和數據粘貼到一個txt文件，並使用下面的代碼它轉換爲.xlsx文件：現在

with open('Galton_height_Data.txt','r') as f: 

data = [] 

for i in f: 
    z = i.strip('\n') 
    z = z.split('\t') 
    data.append(z) 

import pandas as pd 

df = pd.DataFrame(data[1:], columns = data[0]) 

df.to_excel('Galton_Height.xlsx') 

，我想用形象化散點圖中的數據。我試圖想象母親的身高VS以下列方式將孩子的身高：返回

import pandas as pd 
import matplotlib.pyplot as plt 
import seaborn 


df = pd.read_excel("Galton_Height.xlsx") 

ax = df.plot(kind = 'scatter' , x = df['Mother'], y = df['Height']) 

以下錯誤：

`KeyError: '[ 67. 67. 67. 67. 66.5 66.5 66.5 66.5 64. 64. 64. 64.\n 64. 64. 64. 58.5 58.5 58.5 58.5 58.5 58.5 68. 68. 68.\n 68. 68. 68. 68. 66.5 66.5 66.5 66. 65.5 62. 62. 62.\n 62. 62. 62. 62. 62. 61. 67. 67. 66.5 66.5 66.5 65.\n 65. 65. 65. 65. 65. 65. 65. 65. 64.5 64.5 64.5 64.5\n 64.5 64.5 64. 64. 64. 63. 69. 69. 69. 69. 69. 69.\n 69. 69. 68. 68. 68. 67. 67. 67. 65. 65. 65. 65.\n 65. 65. 65. 65.5 64. 64. 63. 63. 63. 63. 63. 63.\n 63. 63. 63. 63. 63. 63. 63. 63. 63.5 63.5 63.5 62.\n 62. 62. 62. 62. 62. 62. 62. 62. 62. 62. 62. 62.\n 62. 62. 62. 62. 61. 69. 69. 69. 69. 69. 67. 67.\n 67. 67. 66. 66. 66. 66. 66. 66. 66. 66. 66. 66.\n 66. 66. 66. 66. 66. 66. 66. 65.5 65.5 65.5 65.5 65.5\n 65.5 65.5 65.5 65.5 65. 65. 65. 65. 65. 64. 64. 64.\n 64. 64. 64. 64. 64. 64.5 64.5 64.5 64.5 64. 64. 64.\n 64.5 64.5 64.5 64.5 64.5 64.5 64.5 63. 63. 63.5 63.5 63.5\n 63.5 63.5 63. 63. 63. 63. 63. 63. 63. 63. 63. 63.\n 63. 63. 63. 62. 62. 62. 62. 62. 62. 62. 62. 62.\n 62. 62.5 62.5 62.5 62.5 62.5 62. 62. 62. 62. 62. 62.\n 62. 61. 58. 58. 69. 69. 69. 69. 69. 69. 69. 69.\n 69. 69. 68. 67. 67. 67. 67. 67. 67. 66.5 66.5 66.5\n 66.5 66.5 66.5 66.5 66.5 66.5 66.5 66.5 65. 65. 65. 65.\n 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65.\n 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65.\n 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65.\n 64.7 64.7 64.7 64.7 64.7 64.7 64.7 64. 64. 64. 64. 64.\n 64. 64. 64. 64. 64. 64. 64.2 64.2 64.2 64.2 64.2 64.\n 64. 64. 64. 64. 64. 64. 64. 64.5 64. 64. 64. 64.\n 64. 64. 64. 64. 64. 64. 64. 64. 64. 63.7 63.7 63.7\n 63.7 63.7 63.7 63.7 63.7 63. 63. 63. 63. 63. 63.5 63.5\n 63.5 63.5 63. 63. 63. 63. 63. 63. 63. 63. 62. 62.\n 62. 62. 62. 62. 62. 62. 62.7 62.7 62.7 62.7 62.7 62.7\n 62.7 62. 62. 62. 61. 61. 60. 60. 60. 60. 60. 60.\n 58.5 58.5 58.5 58. 58. 58. 58. 58. 68.5 68.5 68.5 68.5\n 68.5 68.5 68.5 68.5 68.5 68.5 67. 66. 66. 66. 66. 66.\n 66. 66. 66. 66. 66. 66. 66.7 66.7 66.7 66.7 66.7 66.7\n 66. 66. 66. 66. 66. 66. 66.5 66.5 66.5 66.5 66.5 66.5\n 66.5 66.5 66.5 66.5 66.5 66.5 66.5 66.5 66.5 66. 66. 66.\n 66. 66. 66. 66. 66. 66. 66. 66. 66. 66. 66. 66.\n 66. 65. 65. 65. 65. 65. 65. 65. 64.5 64.5 64.5 64.5\n 64.5 64.5 64.5 64. 64. 64. 64. 63. 63. 63. 63. 63.\n 63. 63. 63. 63. 63. 63.5 63.5 63.5 63.5 63.5 63.5 63.5\n 63.5 63.5 63.5 62. 62. 62. 62. 62. 62. 62. 62. 62.\n 62.5 62.5 62.5 62.5 62.5 62.5 62.5 62.5 62. 62. 62. 62.\n 61. 61. 61. 61. 61. 61. 61. 61. 61. 61. 61. 61.\n 61. 61. 60. 60. 60. 60. 60. 60. 60. 60.5 70.5 70.5\n 67. 67. 67. 66.5 66.5 66.5 66.5 66.5 66.5 66.5 66.5 66.5\n 66.5 65. 65. 65.5 65.5 65.5 65.5 65.5 65.5 65.5 65.5 65.5\n 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65.\n 64. 64. 64. 64. 64. 64. 64. 64. 64. 64. 64. 64.\n 64. 64. 64. 64. 64. 64. 64. 64.5 64. 64. 64. 64.\n 64. 64. 64. 64. 64. 64. 63. 63. 63. 63. 63. 63.\n 63. 63. 63.5 63.5 63.5 63.5 63. 63. 63. 63. 63. 63.\n 63. 63. 63. 63. 63. 63. 63. 63. 63. 63. 63. 63.\n 63. 63.5 63. 63.5 63.5 63.5 63.5 63.5 62.5 62. 62. 62.5\n 61. 61. 61. 61. 61. 60.2 60. 60. 60. 60. 60. 60.\n 60. 60. 60. 60. 60. 59. 59. 59. 59. 59. 59. 59.\n 59. 59. 59. 59. 66.2 66.2 66.2 66.2 66.2 66.5 65. 65.\n 65. 65. 65. 65. 65.5 65.5 65.5 65.5 65.5 65.5 65.5 65.5\n 65.5 65. 65. 65. 65. 65. 65. 65. 65. 65. 65. 65.\n 65. 65. 65. 64. 64. 64. 64. 63.5 63.5 63.5 63.5 63.5\n 63.5 63.5 63.5 63. 63. 63. 62. 62. 62. 62. 62. 61.\n 67. 67. 67. 67. 67. 67. 67. 67. 67. 67. 67. 67.\n 67. 67. 67. 67. 67. 66. 66. 66. 66. 66. 66. 66.\n 66. 66. 66. 66. 65. 65. 65. 65. 65. 65. 65. 65.\n 65.5 65.5 65.5 65.5 65.5 63. 63.5 63.5 63. 63. 63. 63.\n 63. 63. 62.5 62.5 62.5 62.5 62.5 62.5 62.5 61.5 60. 60.\n 60. 60. 60. 59. 59. 59. 59. 59. 59. 59. 59. 59.\n 59. 59. 59. 59. 59. 59. 67. 67. 67. 67. 67. 66.\n 66. 66. 66. 65. 65. 65. 65. 65. 65. 65. 65. 65.\n 65.5 65.5 65. 65. 65. 65. 65. 65. 64. 64. 64. 64.\n 64. 64. 63. 63. 63. 63. 63. 63. 63. 63. 63. 60.\n 60. 60. 60. 60. 64. 64. 64. 64. 64. 64. 64. 64.\n 64. 64. 64. 64. 64. 64. 63. 60. 60. 66. 66. 66.\n 63. 63. 65. 65. 65. 65. 65. 65. 65. 65. ] not in index' 

`

這是母親的高度數據。它看起來像一些值有一個'\ n'，但我認爲我照顧，當我轉換爲xlsx文件。

可能會發生什麼？

Answer 1

對於它的價值，您可以使用pandas解析器來讀取該文件。

df = pd.read_csv('Galton_height_Data.txt', delim_whitespace=True) 

爲了您的情節，通過列名到plot方法。

df.plot(kind='scatter', x='Mother', y='Height')