pandas dtype string
Columns with mixed types are stored with the object dtype. ... 'string': ['foo']}) >>> df.dtypes float float64 int int64 datetime datetime64[ns] string object dtype: ... ,Series and Index are equipped with a set of string processing methods that ... [12]: df.columns.str.lower() Out[12]: Index([' column a ', ' column b '], dtype='object'). ,Notes. To select all numeric types, use np.number or 'number'; To select strings you must use the object dtype, but note that this will return all object dtype ... ,df['id'].astype(basestring) 0 123 1 512 2 zhub1 3 12354.3 4 129 5 753 6 295 7 610 Name: id, dtype: object. share improve this answer. answered Mar 6 '14 at 17: ... ,Update: this has been fixed: from 0.11.1 you passing str / np.str will be equivalent to using object . Use the object dtype: In [11]: pd.read_csv('a', dtype=object, ... ,You can use parameter dtype with str : df = pd.read_csv('sample.csv', dtype=str). , EDIT - sorry, I misread your question. Updated my answer. You can read the entire csv as strings then convert your desired columns to other ...,since strings data types have variable length, it is by default stored as object dtype. If you want to store them as string type, you can do something like this. ,Just want to reiterate this will work in pandas >= 0.9.1: In [2]: read_csv('sample.csv', dtype='ID': object}) Out[2]: ID 0 00013007854817840016671868 1 ...
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 pandas dtype string 相關參考資料
pandas.DataFrame.dtypes — pandas 0.23.4 documentation
Columns with mixed types are stored with the object dtype. ... 'string': ['foo']}) >>> df.dtypes float float64 int int64 datetime datetime64[ns] string object dtype: ... https://pandas.pydata.org Working with Text Data — pandas 0.23.4 documentation
Series and Index are equipped with a set of string processing methods that ... [12]: df.columns.str.lower() Out[12]: Index([' column a ', ' column b '], dtype='object'). https://pandas.pydata.org pandas.DataFrame.select_dtypes — pandas 0.23.4 documentation
Notes. To select all numeric types, use np.number or 'number'; To select strings you must use the object dtype, but note that this will return all object dtype ... https://pandas.pydata.org Pandas: change data type of Series to String - Stack Overflow
df['id'].astype(basestring) 0 123 1 512 2 zhub1 3 12354.3 4 129 5 753 6 295 7 610 Name: id, dtype: object. share improve this answer. answered Mar 6 '14 at 17: ... https://stackoverflow.com Pandas reading csv as string type - Stack Overflow
Update: this has been fixed: from 0.11.1 you passing str / np.str will be equivalent to using object . Use the object dtype: In [11]: pd.read_csv('a', dtype=object, ... https://stackoverflow.com Import pandas dataframe column as string not int or float - Stack ...
You can use parameter dtype with str : df = pd.read_csv('sample.csv', dtype=str). https://stackoverflow.com Pandas read_csv dtype read all columns but few as string - Stack ...
EDIT - sorry, I misread your question. Updated my answer. You can read the entire csv as strings then convert your desired columns to other ... https://stackoverflow.com How to convert column with dtype as object to string in Pandas ...
since strings data types have variable length, it is by default stored as object dtype. If you want to store them as string type, you can do something like this. https://stackoverflow.com Import pandas dataframe column as string not int - Stack Overflow
Just want to reiterate this will work in pandas >= 0.9.1: In [2]: read_csv('sample.csv', dtype='ID': object}) Out[2]: ID 0 00013007854817840016671868 1 ... https://stackoverflow.com |