How to use Python to analyze big data

Python data analysis hello dear,!<

1. Check the data table Python uses the shape function to view the dimensions of the data table, that is, the number of rows and columns. You can use the info function to view the overall information of the data table, and the dtypes function to return the data format. Inull is a function in Python that checks null values, you can check the entire data table, or you can check the null value of a single column, and the result returned is a logical value, including null values and returning false.

Use the unique function to view the unique value and the values function to view the numerical value in the data table. 2. The method of processing null values in data table cleaning python is more flexible, you can use the dropna function to delete the data containing null values in the data table, or you can use the fillna function to fill the null values. In Python, dtype is a function to view the data format, and the corresponding function is the astype function to change the data format, rename is a function to change the column name, the drop duplicates function removes duplicate values, and the replace function implements data replacement.

3. Data preprocessingData preprocessing is to sort out the cleaned data for later statistics and analysis, mainly including the merger, sorting, numerical column, data grouping and labeling of data tables. In Python, you can use the merge function to merge two data tables in the inner way, and there are also left, right, and outer methods. Use the ort values function and the sort index function to complete sorting, the where function to complete data grouping, and the split function to implement columns.

4. Data extraction mainly uses three functions: LOC, ILOC and IX, where the LOC function is extracted by the label value, ILOC is extracted by position, and IX can be extracted by label and position at the same time. In addition to lifting data by tag and location, you can also use specific conditions to extract data according to specific conditions, such as using the loc and isin functions together to extract data according to specified conditions.

5. Data filtering summary Python uses the loc function with the filter conditions to complete the filtering function, and the sum and count functions can also realize the functions of the sumif and countif functions in excel. The main functions used in python are groupby and pivot are functions for classification and summarization, and the use method is very simple, you can specify the column names to be grouped, or you can specify multiple column names at the same time, groupby groups according to the order in which the column names appear. Hope it helps!