Example 1: Extract DataFrame Columns Using Column Names & Square Brackets This example shows how to use the names of our variables and square brackets to subset our pandas DataFrame. Have a look at the following Python code: data_new1=data[['x1','x3','x5']]# Subset dataprint(data_new...
4. Explode Multiple Columns Using DataFrame.explode() Alternatively, You can also useexplode()function to explode multiple columns together using the explode function in pandas DataFrame. It returns DataFrame exploded lists to rows of the subset columns; the index will be duplicated for these rows....
expand=False) --- ValueError Traceback (most recent call last) Cell In[116], line 1 ---> 1 s.index.str.extract("(?P<letter>[a-zA-Z])([0-9]+)", expand=False) File ~/work/pandas/pandas/pandas/core/strings/accessor.py:137, in forbid_nonstring_types.<locals>._forbid_nonstring...
'orange', 'grape']}df_str = pd.DataFrame(data_str)# 判断是否包含特定字符串contains_apple = df_str['Text'].str.contains('apple')# 提取字符串中的数字df_str['Number'] = df_str['Text'].str.extract('(\d+)')print("判断是否包含特定字符串:")print(contains_apple)print("\n提取字符串...
gram_df= food_info[gram_columns]#根据列名,输出对应的每一列print(gram_df.head(3))#只输出前三行 加减乘除计算: print(food_info["Iron_(mg)"])#打印列名为"Iron_(mg)"的这一列div_1000 = food_info["Iron_(mg)"] / 1000#将这一列的值都除以1000print(div_1000)#Adds 100 to each value ...
Change the Order of Pandas DataFrame Columns Difference Between loc and iloc in Pandas DataFrame Pandas Check Column Contains a Value in DataFrame Extract Pandas column value based on another column Drop Single & Multiple Columns From Pandas DataFrame...
...: columns=["first","second"], ...: ) ...: In [11]: pd.MultiIndex.from_frame(df) Out[11]: MultiIndex([('bar','one'), ('bar','two'), ('foo','one'), ('foo','two')], names=['first','second']) 作为一种便利,你可以直接将数组列表传递给Series或DataFrame以自动构建Mult...
请注意,DataFrame 的列是一个索引,因此使用 rename_axis 与columns 参数将更改该索引的名称。 代码语言:javascript 复制 In [95]: df.rename_axis(columns="Cols").columns Out[95]: RangeIndex(start=0, stop=2, step=1, name='Cols') rename 和rename_axis 都支持指定字典、Series 或映射函数,将标签/...
DataFrames are two-dimensional structures that display data in rows and columns. A DataFrame is the Pandas equivalent of a table, as you can see below. Each column in a DataFrame can be considered a Series (i.e., if you extract one column, it becomes a Series). Now, you have both ...
提取字符串中的特定部分:df['column'].str.extract('(pattern)') 分割字符串列:df['column'].str.split('-') 检查字符串是否包含特定子串:df['column'].str.contains('substring') 数据输出 将数据保存为 CSV 文件:df.to_csv('new_data.csv') ...