import pandas as pd d = {'one' : pd.Series([1, 2, 3], index=['a', 'b', 'c']), 'two' : pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])} df = pd.DataFrame(d) #标签检索 print("Access By Label:") print(df.loc['b']) #位置索引 print("Access By ...
The .index attribute provides direct access to the DataFrame index. Use .index.dtype to find out the data type of the index. Use tolist() on .index to convert the index to a Python list. Use .index[position] to get a specific index value by position. Use .get_loc(value) on ....
# import pandasimportpandasaspd# create dataframedf=pd.DataFrame({'Name':['sanjay','suresh','Rahul','Krish','vihan'],'Address':['Haridwar','Mohali','mohali','Mohali','saharanpur']})# Display original dataframeprint(" Original dataframe ")print(df)# Display last index value of 0 inde...
In [1]: dates = pd.date_range('1/1/2000', periods=8) In [2]: df = pd.DataFrame(np.random.randn(8, 4), ...: index=dates, columns=['A', 'B', 'C', 'D']) ...: In [3]: df Out[3]: A B C D 2000-01-01 0.469112 -0.282863 -1.509059 -1.135632 2000-01-02 1.212112...
Write a Pandas program to set a MultiIndex and access specific data using it. Sample Solution: Python Code : importpandasaspd# Create a DataFramedf=pd.DataFrame({'X':[1,6,8,3,7],'Y':[5,2,9,4,1],'Z':['one','one','two','two','one']})# Set MultiIndexdf=df.set_index([...
The string representation(代表) of a Series displaye interactively(交互地) show the index on the left and the value on the right.(索引显示在左边, 值在右边) Since we did not specify(指定) an index for the data, a default one consisting of the integer 0 throught N-1(where N is the ...
df.info() <class 'pandas.core.frame.DataFrame'> RangeIndex: 6040 entries, 0 to 6039 Data columns (total 5 columns): UserID 6040 non-null int64 Gender 6040 non-null object Age 6040 non-null int64 Occupation 6040 non-null int64 Zip-code 6040 non-null object dtypes: int64(3), object(2...
DataFrame将以尽量模仿 REPL 输出的方式写入。index_label将放在第二行而不是第一行。您可以通过将to_excel()中的merge_cells选项设置为False将其放在第一行。 df.to_excel("path_to_file.xlsx", index_label="label", merge_cells=False)• 1
Creating aDataFrameby passing a numpy array, with a datetime index and labeled columns: In [6]:dates=pd.date_range('20130101',periods=6)In [7]:datesOut[7]:DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04','2013-01-05', '2013-01-06'],dtype='datetime64...
To access more than one row, use double brackets and specify the indexes, separated by commas:df.iloc[[0, 2]]Specify columns by including their indexes in another list:df.iloc[[0, 2], [0, 1]]You can also specify a slice of the DataFrame with from and to indexes, separated by a ...