Pandas

Applications in pandas

“pandas is kind of excel in python”

1. Dataframe

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   # 创建一个示例 DataFrame
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   df = pd.DataFrame({
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   'A': [1, 2, 3],
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   'B': [4, 5, 6]
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   })

2. Dataframe to numpy: df.to_numpy()

3. Numpy to Dataframe: df = pd.Dataframe(array)

4. drop some columns:

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   # drop by column name list
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   column_list = ['1', '2', '3']
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   df = df.drop(column_list, axis=1) # drop some columns

5. rename column:

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   # rename by column name:
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   df.rename(columns={"A":"a", "B":"b"})
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   # rename by index
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   df.rename(index={0: "x", 1: "y"})

6. get column name list:

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   column_list = df.columns # return "Index['column1', 'column2'...'column10']"

7. get continuous part of dataframe

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   df_part1 = df.iloc[:, :6] # first 5 columns of df
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   df_part2 = df.iloc[:5, :] # first 5 rows of df
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   df_index = df.iloc[1, 2] # element at index (1, 2)

8. modify a column

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   df['column_name'] = df['column_name'].map({'ClassA': 1, 'ClassB': 2}) # mapping Label to Number
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   df['column_name'] = df['column_name'].map(lambda x: x * 2) # mapping element using lambda

9. form a dataframe by multiple arrays

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   df = pd.DataFrame({
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      'Column1': array1,
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      'Column2': array2
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   })

10. data frame concat

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feature_list = df.columns
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new_df = df[feature_list[0:3] + [df.columns[-1]]]