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### Pandas #### Pandas + Pandas (Panel data & data analysis), Numpy + Pandas **Series** **DataFrame** + [Pandas ](https://www.pypandas.cn/docs/getting_started/dsintro.html#dataframe) #### Pandas + Pandas + SQL Excel ; + ; + ; + , Pandas + Pandas 1. NaN 2. DataFrame 3. SeriesDataFrame 4. group by-- 5. Python NumPy DataFrame 6. 7. merge**join** 8. reshape**pivot** 9. 10. IO CSV Excel HDF5 / 11. #### 1. Series ****Python + : `pd.Series(self, data=None, index=None, dtype=None, name=None, copy=False, fastpath=False)` + data 1. **Python ** : `pd.Series({'b': 1, 'a': 0, 'c': 2})` 2. **** : data index data index [0, ..., len(data) - 1] 3. **5** : data Series + Series ```python import pandas as pd import numpy as np index = ["stu0", "stu1", "stu2", "stu3"] value = [ ["", 13, 1], ["", 32, 2], ["", 23, 1], ["", 12, 1], ] se = pd.Series(index=index, data=value) print(se) print(se.ndim) # 1 print(se.dtype) # object print(se.shape) # (4,) print(se.index) # Index(['stu0', 'stu1', 'stu2', 'stu3'], dtype='object') print(se.values) # [list(['', 13, 1]) list(['', 32, 2]) list(['', 23, 1]) list(['', 12, 1])] ``` 2. DataFrame **** Excel SQL Series DataFrame Pandas Series + `pd.DataFrame(self, data=None, index: Optional[Axes] = None, columns: Optional[Axes] = None, dtype: Optional[Dtype] = None, copy: bool = False,)` + | | | | ----------- | ---------------- | | **data** | | | **index** | | | **columns** | | | **copy** | | + DataFrame 1. ndarraySeries 2. numpy.ndarray 3. 1. Series 2. DataFrame + 1. ```python import pandas as pd # DataFrame # # index = ["stu0", "stu1", "stu2", "stu3"] # columns = ["name", "age", "group"] # value = [ ["", 13, 1], ["", 32, 2], ["", 23, 1], ["", 12, 1], ] df = pd.DataFrame(data=value, index=index, columns=columns) """ name age group stu0 13 1 stu1 32 2 stu2 23 1 stu3 12 1 """ ``` 2. ( key, values) ```python import pandas as pd # DataFrame # index = ["stu0", "stu1", "stu2", "stu3"] dict1 = { "name": ["", "", "", "",], "age": [12, 21, 32, 32], "group": [1, 2, 1, 1], } df1 = pd.DataFrame(dict1, index=index) print(df1) """ name age group stu0 12 1 stu1 21 2 stu2 32 1 stu3 32 1 """ ``` + + **shape** : + **ndim** : + **size** : () + **dtypes** : DataFrame , , object string + **values** : + **index** : + **columns** : + 1. : `df.columns = ` 2. : `df.rename(columns={"1": "1", "2": "2"}, inplace=True)` 3. : `df.rename(index={"1": "1", "2": "2"}, inplace=True)` #### Pandas + Pandas DataFrame . + Pandas csvtxtexcel (.xlsx .xls) ##### + `pd.read_()` + | | | | ------------------------------- | ------------------------------------------------------------ | | **filepath_or_buffer** | FilePathOrBuffer : | | **sep=","****delimiter=None** | delimiter sep | | **encoding** | | | **header="infer"** | , **header="2"** | | **index_col=None** | | | **nrows=None** | , | | **usecols=None** | None
1. **None**
2. **int**
3. **list** int
4. **string** excel"A:F"AF"A,D,E:H"ADEH | | **names=None** | , | | **sheet_name=0** | Excel0 | | **skiprows=None** | | | **keep_default_na** | True | | **dtype** | {a: np.float64, b: np.int32} | ##### + : `DF_name.to_()` + | | | | -------------------------------------------------- | ------------------------------------------------------------ | | **path_or_buf: Optional[FilePathOrBuffer] = None** | | | **sep: str = ","** | | | **float_format: Optional[str] = None** | %.0f | | **header: Union[bool_t, List[str]] = True** | ()True | | **index: bool_t = True** | ()True | | **columns: Optional[Sequence[Label]] = None** | ,, | | **mode: str = "w"** | "w" | | **sheet_name** | **Excel**,"Sheet1"
**int** 0 ()
| + : excel + dataframe excel sheet + sheet + ```python import numpy as np import pandas as pd index = ["stu0", "stu1", "stu2", "stu3"] dict1 = { "name": ["", "", "", "", ], "age": [12, 21, 32, 32], "group": [1, 2, 1, 1], } df1 = pd.DataFrame(dict1, index=index) writer = pd.ExcelWriter('../read_excel/.xlsx') df1.to_excel( excel_writer=writer, index=False, sheet_name="0" ) df1.to_excel( excel_writer=writer, index=False, header=False, startrow=5, sheet_name="0" ) writer.close() ``` #### DataFrame ##### DataFrame 1. + ****DataFrame Series DataFrame DataFrame 1. key 2. + + : `df_name[ [1, 2, ...] ]` + : `df_name[ [1, 2, ...] ][ 1: 2]` `df_name[ 1 : 2][ [1, 2, ...] ]` + ```python import pandas as pd index = ["stu0", "stu1", "stu2", "stu3"] columns = ["name", "age", "group"] # value = [["", 19, 1], ["", 20, 2], ["", 19, 1], ["", 17, 2]] df = pd.DataFrame(index=index, columns=columns, data=value) out = df["name"] # print(df) """ name age group stu0 19 1 stu1 20 2 stu2 19 1 stu3 17 2 """ # 1. print(out["stu1"]) # # 2. print(out[2]) # # 3. print(out["stu2":"stu2"]) """ stu2 Name: name, dtype: object """ # 4. print(out[2:3]) """ stu2 Name: name, dtype: object """ # 5. print(out[["stu1"]]) """ stu1 Name: name, dtype: object """ # 6. print(out[[2]]) """ stu2 Name: name, dtype: object """ # 7. head print(out.head(3)) """ stu0 stu1 stu2 Name: name, dtype: object """ # 8. tail print(out.tail(3)) """ stu1 stu2 stu3 Name: name, dtype: object """ # print(out["stu0":"stu3"]) """ stu0 stu1 stu2 stu3 Name: name, dtype: object """ print(out[["stu1", "stu2"]]) """ stu1 stu2 Name: name, dtype: object """ print(out[1:3]) """ stu1 stu2 Name: name, dtype: object """ ``` 2. loc iloc + `DF_name.loc[, ]` + **** : : ; / + **** : : ; / + `DF_name.iloc[]` ,

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