在这个Python教程中，我们将讨论向pandas DataFrame对象添加或插入一条或多条记录的五大方法。那么，让我们开始讨论吧。
向pandas数据框架添加行的方法
让我们首先创建一个样本的pandas DataFrame对象开始，然后我们将不断使用以下方法向其添加一条或多条记录:
# Import pandas Python module
import pandas as pd
# Create a sample pandas DataFrame object
df = pd.DataFrame({'RegNo': [111, 112, 113, 114, 115],
'Name': ['Gautam', 'Tanya', 'Rashmi', 'Kirti', 'Ravi'],
'CGPA': [8.85, 9.03, 7.85, 8.85, 9.45],
'Dept': ['ECE', 'ICE', 'IT', 'CSE', 'CHE'],
'City': ['Jalandhar','Ranchi','Patna','Patiala','Rajgir']})
# Print the created pandas DataFrame
print('Sample pandas DataFrame:\n')
print(df)
输出
Sample pandas DataFrame:
RegNo Name CGPA Dept City
0 111 Gautam 8.85 ECE Jalandhar
1 112 Tanya 9.03 ICE Ranchi
2 113 Rashmi 7.85 IT Patna
3 114 Kirti 8.85 CSE Patiala
4 115 Ravi 9.45 CHE Rajgir
方法#1
添加一个pandas系列对象作为行到现有的pandas DataFrame对象中。
# Create a pandas Series object with all the column values passed as a Python list
s_row = pd.Series([116,'Sanjay',8.15,'ECE','Biharsharif'], index=df.columns)
# Append the above pandas Series object as a row to the existing pandas DataFrame
# Using the DataFrame.append() function
df = df.append(s_row,ignore_index=True)
# Print the modified pandas DataFrame object after addition of a row
print('Modified Sample pandas DataFrame:\n')
print(df)
输出
Modified Sample pandas DataFrame:
RegNo Name CGPA Dept City
0 111 Gautam 8.85 ECE Jalandhar
1 112 Tanya 9.03 ICE Ranchi
2 113 Rashmi 7.85 IT Patna
3 114 Kirti 8.85 CSE Patiala
4 115 Ravi 9.45 CHE Rajgir
5 116 Sanjay 8.15 ECE Biharsharif
方法 #2
将一个Python字典作为一行添加到现有的pandas DataFrame对象中。
# Create a Python dictionary object with all the column values
d_row = {'RegNo':117,'Name':"Sarthak",'CGPA':8.88,'Dept':"ECE",'City':"Allahabad"}
# Append the above Python dictionary object as a row to the existing pandas DataFrame
# Using the DataFrame.append() function
df = df.append(d_row,ignore_index=True)
# Print the modified pandas DataFrame object after addition of a row
print('Modified Sample pandas DataFrame:\n')
print(df)
输出
Modified Sample pandas DataFrame:
RegNo Name CGPA Dept City
0 111 Gautam 8.85 ECE Jalandhar
1 112 Tanya 9.03 ICE Ranchi
2 113 Rashmi 7.85 IT Patna
3 114 Kirti 8.85 CSE Patiala
4 115 Ravi 9.45 CHE Rajgir
5 116 Sanjay 8.15 ECE Biharsharif
6 117 Sarthak 8.88 ECE Allahabad
注意： 在传递Python字典或pandas系列时，请将DataFrame.append() 函数的ignore_index 参数设置为True ，否则，会出现错误。
方法 #3
使用DataFrame.loc[] 方法将一个 Python list 对象作为行添加到现有的 pandas DataFrame 对象中。
# Create a Python list object with all the column values
l_row = [118,"Kanika",7.88,"EE","Varanasi"]
# Append the above Python list object as a row to the existing pandas DataFrame
# Using the DataFrame.loc[]
df.loc[7] = l_row
# Print the modified pandas DataFrame object after addition of a row
print('Modified Sample pandas DataFrame:\n')
print(df)
输出
Modified Sample pandas DataFrame:
RegNo Name CGPA Dept City
0 111 Gautam 8.85 ECE Jalandhar
1 112 Tanya 9.03 ICE Ranchi
2 113 Rashmi 7.85 IT Patna
3 114 Kirti 8.85 CSE Patiala
4 115 Ravi 9.45 CHE Rajgir
5 116 Sanjay 8.15 ECE Biharsharif
6 117 Sarthak 8.88 ECE Allahabad
7 118 Kanika 7.88 EE Varanasi
方法 #4
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。
# Create a new pandas DataFrame object
df2 = pd.DataFrame({'RegNo': [119, 120, 121],
'Name': ['Gaurav', 'Thaman', 'Radha'],
'CGPA': [8.85, 9.03, 7.85],
'Dept': ['ECE', 'ICE', 'IT'],
'City': ['Jalandhar','Ranchi','Patna']})
# Print the newly created pandas DataFrame object
print('New pandas DataFrame:\n')
print(df2)
# Append the rows of the above pandas DataFrame to the existing pandas DataFrame
# Using the DataFrame.append()
df = df.append(df2,ignore_index=True)
# Print the modified pandas DataFrame object after addition of rows
print('\nModified Sample pandas DataFrame:\n')
print(df)
输出
New pandas DataFrame:
RegNo Name CGPA Dept City
0 119 Gaurav 8.85 ECE Jalandhar
1 120 Thaman 9.03 ICE Ranchi
2 121 Radha 7.85 IT Patna
Modified Sample pandas DataFrame:
RegNo Name CGPA Dept City
0 111 Gautam 8.85 ECE Jalandhar
1 112 Tanya 9.03 ICE Ranchi
2 113 Rashmi 7.85 IT Patna
3 114 Kirti 8.85 CSE Patiala
4 115 Ravi 9.45 CHE Rajgir
5 116 Sanjay 8.15 ECE Biharsharif
6 116 Sanjay 8.15 ECE Biharsharif
7 118 Kanika 7.88 EE Varanasi
8 119 Gaurav 8.85 ECE Jalandhar
9 120 Thaman 9.03 ICE Ranchi
10 121 Radha 7.85 IT Patna
方法#5
使用DataFrame.iloc[] 方法在特定的索引位置向现有的pandas DataFrame对象中添加一条记录。
# Create a Python list object with all the column values
i_row = [122,"Zahir",6.88,"ME","Kolkata"]
# Append the above Python list object as a row to the existing pandas DataFrame
# At index 2 using the DataFrame.iloc[]
df.iloc[2] = i_row
# Print the modified pandas DataFrame object after addition of a row
print('Modified Sample pandas DataFrame:\n')
print(df)
输出
Modified Sample pandas DataFrame:
RegNo Name CGPA Dept City
0 111 Gautam 8.85 ECE Jalandhar
1 112 Tanya 9.03 ICE Ranchi
2 122 Zahir 6.88 ME Kolkata
3 114 Kirti 8.85 CSE Patiala
4 115 Ravi 9.45 CHE Rajgir
5 116 Sanjay 8.15 ECE Biharsharif
6 116 Sanjay 8.15 ECE Biharsharif
7 118 Kanika 7.88 EE Varanasi
8 119 Gaurav 8.85 ECE Jalandhar
9 120 Thaman 9.03 ICE Ranchi
10 121 Radha 7.85 IT Patna
注意:在使用DataFrame.iloc[] 方法时请注意，因为它将在该索引位置用新行替换现有行。
总结
在本教程中，我们已经学习了向现有的pandas DataFrame对象添加或插入一条或多条记录的五大方法。希望你已经很好地理解了上面讨论的内容，并准备在你自己的数据分析项目中使用这些方法。谢谢你的阅读!请继续关注我们，了解更多关于Python编程的精彩学习资源。
