pandas yes python One of the most powerful tools for data mining and data analysis , Support is similar to SQL The increase of database , Delete , check , change , And with a wealth of data processing functions , Support the analysis function of time series , Support flexible handling of missing data .pandas The basic data structure is Series and DataFrame,series It's sequence , Similar to a one-dimensional array ,dataframe It's equivalent to a two-dimensional table , Similar to a two-dimensional array , Each of its columns is equivalent to one series, For positioning series Elements in ,pandas Provided index object , each series There will be a corresponding index, Used to mark different elements ,index The content of is not necessarily a number , It can also be letters , Chinese, etc , be similar to SQL Primary key of , allied ,dataframe Equivalent to having more than one of the same index Of series The combination of ( It's essentially series Container for ), each series All have a unique header , Used to identify different series.

import pandas as pd s = pd.Series([1, 2, 3], index=['a', 'b', 'c']) d =
pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=['a', 'b', 'c']) d2 =
pd.DataFrame(s) d.head() d.describe() print(d) print(d2)
#pd.read_excel('data.xls') #pd.read_csv('data.csv', encoding='utf-8')

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