Data list: the basis of data analysis A data list
本帖最後由 hmdahsan113 於 2024-9-23 11:35 編輯simply an ordered collection of data. It can be a set of numbers, text, dates, or other types of data. In data analysis, data lists are the basis for various calculations, statistics, and analysis. How to represent data lists One-dimensional array: The most common form of data lists, with an index to identify each element. For example, in Python, a list can be used to represent a one-dimensional array. Two-dimensional array: An array composed of multiple one-dimensional arrays, usually used to represent tabular data.
In Python, ndarray in the NumPy library can be used to Email List represent a two-dimensional array. Data frame: It is a tabular data structure that contains a set of ordered columns, each of which can have a different data type. In Python, the Pandas library provides a powerful DataFrame function. The role of data lists in data analysis Data storage: Store the collected data in a list for subsequent processing. Data cleaning: Clean the data to remove outliers, missing values, etc. Data conversion: Convert data into a form suitable for analysis, such as converting text data into numerical data.
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Data calculation: Perform various calculations on the data, such as sum, average, standard deviation, etc. Data visualization: Visualize the data to understand it more intuitively. Machine learning: Input the data as features into the machine learning model for training and prediction. Data list example Python # Python example import numpy as np import pandas as pd # One-dimensional array numbers = # Two-dimensional array matrix = np.array([, ]) # DataFrame data = {'Name': ['Zhang San', 'Li Si', 'Wang Wu'], 'Age': } df = pd.DataFrame(data) Use code with caution. Application of data lists in different fields Financial field: stock prices, trading volume, customer information, etc.
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