使用np.select函数选择两个列:df['选择结果'] = np.select(conditions, choices, default='col1等于col2') 这样,就可以在DataFrame中添加一个新的列,该列根据条件选择两个列的值。 使用np.select选择两个pandas列的应用场景: 数据清洗:根据不同的条件对数据进行分类或标记。 数据转换:根据条件将数据转换为不同...
df.query("one in @items")# df.query("one == @items", parser='pandas')# df.query("one in ['b', 'd']")# df.query("one == ['b', 'd']", parser='pandas') Note Yes, the default parser is'pandas', but it is important to highlight this syntax isn't conventionally python....
importnumpyasnpimportpandasaspd df = pd.DataFrame( data=np.linspace([0]*3, [1]*3,10, axis=0), index=pd.MultiIndex.from_product([['A','B'],range(5)]), columns=[*'xye'], ) out = df.loc[(df.index.get_level_values(0) =='A') & (df['x'].between(.1,.4...
The goal is to randomly select columns from the above DataFrame across 4 different cases. 4 Cases to Randomly Select Columns in Pandas DataFrame Case 1: randomly select a single column To randomly select a single column, simply adddf = df.sample(axis=”columns”)to the code: Copy importpan...
...i + 1 Next i rng.RemoveDuplicates Columns:=(Cols), Header:=xlYes End Sub 这里使用了当前区域,假设标题位于第一行...如果只想删除指定列(例如第1、2、3列)中的重复项,那么可以使用下面的代码: Sub DeDupeColSpecific() Cells.RemoveDuplicates Columns:=Array...(1, 2, 3), Header:=x...
First, I import the Pandas library, and read the dataset into a DataFrame. Here are the first 5 rows of the DataFrame: wine_df.head() I rename the columns to make it easier for me call the column names for future operations.
df.tail(2)#获取后2行数据#2.数据列的的获取df["name"]#df+列名称df.name#此种方法列名称不能有空格df[["name","age"]]#通过列表选取多列#对于seriesdf["赋值"][0:10]#表示选取series的前9列#此刻需要注意的是如果名中含有空格,直接选取会报错如df['温度 ℃']df.rename(columns={'温度 ℃':'温...
nan_values = df[df.isna().any(axis=1)]print(nan_values) Once you run the code, you’ll get all the rows with the NaNs under the entire DataFrame (i.e., under both the ‘first_set‘ as well as the ‘second_set‘ columns): ...
# SQLSELECT DISTINCT column_a FROM table_df# Pandastable_df['column_a'].drop_duplicates() SELECT a as b 如果你想重命名一个列,使用.rename(): # SQLSELECT column_a as Apple, column_b as Banana FROM table_df# Pandastable_df[['column_a', 'column_b']].rename(columns={'column_a':...
The code sample selects the last 2 columns of theDataFrame. Notice that we used-nbetween the square brackets. If you have to do this often, define a reusable function. main.py importpandasaspd df=pd.DataFrame({'name':['Alice','Bobby','Carl','Dan','Ethan'],'experience':[1,1,5,7...