read_excel('学生成绩汇总表.xlsx') print(df) 实例10:数据分箱:对数据进行分箱统计 import pandas as pd # 首先创建一个空的DataFrame df = pd.DataFrame(columns=['分箱']) # 然后建立一个列表数据,列表里面是人的姓名信息 box_list = [1, 4, 6, 7, 10, 13, 19, 20,
s_from_numpy = pd.Series(np_array)# 从NumPy数组创建Series (默认索引) print(" --- Series from NumPy Array (default index) ---") print(s_from_numpy) # 输出: # 0 1.1 # 1 2.2 # 2 3.3 # 3 4.4 # 4 5.5 # dtype: float64 # 指定索引和名称 (name 属性用于标识 Series 本身) s_fr...
columns=['feature_one','feature_two','feature_three','feature_four'], index=['one','two','three']) # 输出 s_data print(s_data) # 访问第 1 列 print("访问第 1 列") print(s_data["feature_one"]) # 访问第 1 行 print("访问第 1 行") print(s_data.loc["one"]) # 访问第 ...
DataFrame(data = weather_data, columns=['date', 'temperature', 'humidity']) weather_df 本次输出与使用字典创建的DataFrame一样,与上述不同的是: 使用元组列表的时候,我们在使用pd.DataFrame()方法的时候需要传入参数columns以指定列名,columns列表的顺序也直接决定了生成的DataFrame列的顺序。 3. 使用字典列表...
Replace NaN with a blank string in specific columns by selecting them before applyingfillna(). Applyfillna('')to the entire DataFrame to replace NaN in all columns at once. Thereplace()function can also be used to replace NaN values with an empty string by specifyingnp.nan. ...
To split column into multiple columns by comma, we will use thesplit()method. By default, a string is split with a space between two words but if we want to split a string with any other character, we need to pass the specific character insidestr.split()method. Here, for splitting a...
DataFrame(d) # Display original DataFrame print("Original DataFrame:\n",df,"\n") # Defining columns cols=[('c','a'),('c','b')] # Adding column names df.columns=pd.MultiIndex.from_tuples(cols) # Display result print("Result:\n",df) ...
It shows that our example data consists of six rows and the three columns “x1”, “x2”, and “x3”.In addition, we have to create a list that we can add as a new column to our data set.new_col = ['a', 'b', 'c', 'd', 'e', 'f'] # Create example list print(new_...
Along with the data, you can optionally passindex(row labels) andcolumns(column labels) arguments. If you pass an index and / or columns, you are guaranteeing the index and / or columns of the resulting DataFrame. Thus, a dict of Series plus a specific index will discard all data not ...
Having specificdtypes In [12]:df2.dtypesOut[12]:A float64B datetime64[ns]C float32D int32E categoryF objectdtype: object If you’re using IPython, tab completion for column names (as well as public attributes) is automatically enabled. Here’s a subset of the attributes that will be ...