如何在Pandas中创建一个空的DataFrame并向其添加行和列
让我们讨论一下如何在Pandas n Python中创建一个空的DataFrame并向其添加行和列。我们有多种方法可以完成这个任务。这里我们将讨论以下部分。
- 在Pandas中创建一个空的Dataframe
- 在Pandas中向数据框架添加行
- 在Pandas中向数据框架添加行
创建空的数据框架
# import pandas library as pd
import pandas as pd
# create an Empty DataFrame object
df = pd.DataFrame()
print(df)
输出:
Empty DataFrame
Columns: []
Index: []
添加列到数据框架
示例 1:
创建一个完整的空的DataFrame,没有任何列名或索引,然后在Pandas中一个一个地追加列到它。
# import pandas library as pd
import pandas as pd
# create an Empty DataFrame object
df = pd.DataFrame()
print(df)
# append columns to an empty DataFrame
df['Name'] = ['Ankit', 'Ankita', 'Yashvardhan']
df['Articles'] = [97, 600, 200]
df['Improved'] = [2200, 75, 100]
df
输出:
示例 2:
这个方法将创建一个新的Dataframe,并在旧的Dataframe中使用Pandas的assign添加一个新的列。
# Import pandas package
import pandas as pd
# Define a dictionary containing Students data
data = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'],
'Height': [5.1, 6.2, 5.1, 5.2],
'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Using 'Address' as the column name and equating it to the list
df2 = df.assign(address=['Delhi', 'Bangalore', 'Chennai', 'Patna'])
# Observe the result
print(df2)
输出:
将行添加到数据框中
示例 1:
创建一个只有列名的空的DataFrame,然后用append()方法将行一个一个地追加到它上面。
# import pandas library as pd
import pandas as pd
# create an Empty DataFrame
# object With column names only
df = pd.DataFrame(columns = ['Name', 'Articles', 'Improved'])
print(df)
# append rows to an empty DataFrame
df = df.append({'Name' : 'Ankit', 'Articles' : 97, 'Improved' : 2200},
ignore_index = True)
df = df.append({'Name' : 'Aishwary', 'Articles' : 30, 'Improved' : 50},
ignore_index = True)
df = df.append({'Name' : 'yash', 'Articles' : 17, 'Improved' : 220},
ignore_index = True)
df
输出:
示例 2:
用列名和索引创建一个空的DataFrame,然后用loc[]方法将行一个一个地追加到其中。
# import pandas library as pd
import pandas as pd
# create an Empty DataFrame object With
# column names and indices
df = pd.DataFrame(columns = ['Name', 'Articles', 'Improved'],
index = ['a', 'b', 'c'])
print("Empty DataFrame With NaN values : \n\n", df)
# adding rows to an empty
# dataframe at existing index
df.loc['a'] = ['Ankita', 50, 100]
df.loc['b'] = ['Ankit', 60, 120]
df.loc['c'] = ['Harsh', 30, 60]
df
输出: