243 lines
7.2 KiB
Markdown
243 lines
7.2 KiB
Markdown
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# 向熊猫数据框架添加行的 5 种简单方法
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> 原文：<https://www.askpython.com/python-modules/pandas/add-rows-to-dataframe>
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在本 Python 教程中，我们将讨论向 pandas DataFrame 对象添加或插入一行或多行的前五种方法。那么，我们开始讨论吧。
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* * *
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## 向 Pandas 数据帧添加行的方法
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让我们首先创建一个示例 pandas DataFrame 对象，然后我们将使用以下方法向它添加一行或多行。
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```py
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# Import pandas Python module
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import pandas as pd
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# Create a sample pandas DataFrame object
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df = pd.DataFrame({'RegNo': [111, 112, 113, 114, 115],
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'Name': ['Gautam', 'Tanya', 'Rashmi', 'Kirti', 'Ravi'],
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'CGPA': [8.85, 9.03, 7.85, 8.85, 9.45],
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'Dept': ['ECE', 'ICE', 'IT', 'CSE', 'CHE'],
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'City': ['Jalandhar','Ranchi','Patna','Patiala','Rajgir']})
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# Print the created pandas DataFrame
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print('Sample pandas DataFrame:\n')
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print(df)
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```
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**输出:**
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```py
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Sample pandas DataFrame:
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RegNo Name CGPA Dept City
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0 111 Gautam 8.85 ECE Jalandhar
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1 112 Tanya 9.03 ICE Ranchi
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2 113 Rashmi 7.85 IT Patna
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3 114 Kirti 8.85 CSE Patiala
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4 115 Ravi 9.45 CHE Rajgir
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```
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### 方法 1
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将 pandas 系列对象作为一行添加到现有的 pandas DataFrame 对象中。
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```py
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# Create a pandas Series object with all the column values passed as a Python list
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s_row = pd.Series([116,'Sanjay',8.15,'ECE','Biharsharif'], index=df.columns)
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# Append the above pandas Series object as a row to the existing pandas DataFrame
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# Using the DataFrame.append() function
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df = df.append(s_row,ignore_index=True)
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# Print the modified pandas DataFrame object after addition of a row
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print('Modified Sample pandas DataFrame:\n')
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print(df)
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```
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**输出:**
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```py
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Modified Sample pandas DataFrame:
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RegNo Name CGPA Dept City
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0 111 Gautam 8.85 ECE Jalandhar
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1 112 Tanya 9.03 ICE Ranchi
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2 113 Rashmi 7.85 IT Patna
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3 114 Kirti 8.85 CSE Patiala
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4 115 Ravi 9.45 CHE Rajgir
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5 116 Sanjay 8.15 ECE Biharsharif
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```
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### 方法 2
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将一个 [Python 字典](https://www.askpython.com/python/dictionary/python-dictionary-comprehension)作为一行添加到现有的 pandas DataFrame 对象中。
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```py
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# Create a Python dictionary object with all the column values
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d_row = {'RegNo':117,'Name':"Sarthak",'CGPA':8.88,'Dept':"ECE",'City':"Allahabad"}
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# Append the above Python dictionary object as a row to the existing pandas DataFrame
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# Using the DataFrame.append() function
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df = df.append(d_row,ignore_index=True)
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# Print the modified pandas DataFrame object after addition of a row
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print('Modified Sample pandas DataFrame:\n')
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print(df)
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```
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**输出:**
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```py
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Modified Sample pandas DataFrame:
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RegNo Name CGPA Dept City
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0 111 Gautam 8.85 ECE Jalandhar
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1 112 Tanya 9.03 ICE Ranchi
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2 113 Rashmi 7.85 IT Patna
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3 114 Kirti 8.85 CSE Patiala
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4 115 Ravi 9.45 CHE Rajgir
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5 116 Sanjay 8.15 ECE Biharsharif
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6 117 Sarthak 8.88 ECE Allahabad
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```
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**注意:**在传递 Python 字典或熊猫系列时，请将`DataFrame.append()`函数的`ignore_index`参数设置为`True`，否则会抛出错误。
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### 方法 3
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使用`DataFrame.loc[]`方法将 Python 列表对象作为一行添加到现有的 pandas DataFrame 对象中。
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```py
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# Create a Python list object with all the column values
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l_row = [118,"Kanika",7.88,"EE","Varanasi"]
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# Append the above Python list object as a row to the existing pandas DataFrame
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# Using the DataFrame.loc[]
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df.loc[7] = l_row
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# Print the modified pandas DataFrame object after addition of a row
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print('Modified Sample pandas DataFrame:\n')
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print(df)
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```
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**输出:**
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```py
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Modified Sample pandas DataFrame:
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RegNo Name CGPA Dept City
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0 111 Gautam 8.85 ECE Jalandhar
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1 112 Tanya 9.03 ICE Ranchi
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2 113 Rashmi 7.85 IT Patna
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3 114 Kirti 8.85 CSE Patiala
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4 115 Ravi 9.45 CHE Rajgir
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5 116 Sanjay 8.15 ECE Biharsharif
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6 117 Sarthak 8.88 ECE Allahabad
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7 118 Kanika 7.88 EE Varanasi
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```
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### 方法 4
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使用`DataFrame.append()`函数将一个 pandas DataFrame 对象的行添加到另一个 pandas DataFrame 对象中。
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```py
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# Create a new pandas DataFrame object
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df2 = pd.DataFrame({'RegNo': [119, 120, 121],
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'Name': ['Gaurav', 'Thaman', 'Radha'],
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'CGPA': [8.85, 9.03, 7.85],
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'Dept': ['ECE', 'ICE', 'IT'],
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'City': ['Jalandhar','Ranchi','Patna']})
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# Print the newly created pandas DataFrame object
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print('New pandas DataFrame:\n')
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print(df2)
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# Append the rows of the above pandas DataFrame to the existing pandas DataFrame
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# Using the DataFrame.append()
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df = df.append(df2,ignore_index=True)
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# Print the modified pandas DataFrame object after addition of rows
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print('\nModified Sample pandas DataFrame:\n')
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print(df)
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```
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**输出:**
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```py
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New pandas DataFrame:
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RegNo Name CGPA Dept City
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0 119 Gaurav 8.85 ECE Jalandhar
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1 120 Thaman 9.03 ICE Ranchi
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2 121 Radha 7.85 IT Patna
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Modified Sample pandas DataFrame:
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RegNo Name CGPA Dept City
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0 111 Gautam 8.85 ECE Jalandhar
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1 112 Tanya 9.03 ICE Ranchi
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2 113 Rashmi 7.85 IT Patna
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3 114 Kirti 8.85 CSE Patiala
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4 115 Ravi 9.45 CHE Rajgir
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5 116 Sanjay 8.15 ECE Biharsharif
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6 116 Sanjay 8.15 ECE Biharsharif
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7 118 Kanika 7.88 EE Varanasi
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8 119 Gaurav 8.85 ECE Jalandhar
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9 120 Thaman 9.03 ICE Ranchi
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10 121 Radha 7.85 IT Patna
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```
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### 方法 5
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使用`DataFrame.iloc[]`方法在现有 pandas DataFrame 对象的特定索引位置添加一行。
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```py
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# Create a Python list object with all the column values
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i_row = [122,"Zahir",6.88,"ME","Kolkata"]
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# Append the above Python list object as a row to the existing pandas DataFrame
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# At index 2 using the DataFrame.iloc[]
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df.iloc[2] = i_row
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# Print the modified pandas DataFrame object after addition of a row
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print('Modified Sample pandas DataFrame:\n')
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print(df)
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```
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**输出:**
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```py
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Modified Sample pandas DataFrame:
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RegNo Name CGPA Dept City
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0 111 Gautam 8.85 ECE Jalandhar
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1 112 Tanya 9.03 ICE Ranchi
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2 122 Zahir 6.88 ME Kolkata
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3 114 Kirti 8.85 CSE Patiala
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4 115 Ravi 9.45 CHE Rajgir
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5 116 Sanjay 8.15 ECE Biharsharif
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6 116 Sanjay 8.15 ECE Biharsharif
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7 118 Kanika 7.88 EE Varanasi
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8 119 Gaurav 8.85 ECE Jalandhar
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9 120 Thaman 9.03 ICE Ranchi
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10 121 Radha 7.85 IT Patna
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```
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**注意:**使用`DataFrame.iloc[]`方法时请小心，因为它会用新行替换索引位置的现有行。
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## 结论
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在本教程中，我们已经学习了在现有的 pandas DataFrame 对象中添加或插入一行或多行的前五种方法。希望你已经很好地理解了上面讨论的东西，并准备在自己的数据分析项目中使用这些方法。感谢阅读！请继续关注我们，获取更多关于 Python 编程的精彩学习资源。
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