python:如何用 pandas.DataFrame.dropna() 刪除空列(axis=0) 空欄(axis=1) ; df_drop0 = df.dropna(axis=0, how=’all’)

pandas.DataFrame.dropna()官網說明

CSDN的說明

dropna(axis=0, how=’any’, thresh=None, subset=None, inplace=False)

axis{0 or ‘index’, 1 or ‘columns’}, default 0

• 0, or ‘index’ : Drop rows which contain missing values.

• 1, or ‘columns’ : Drop columns which contain missing value.

how{‘any’, ‘all’}, default ‘any’

• ‘any’ : If any NA values are present, drop that row or column.
• ‘any’: 只要有一個NA,就整列(欄)刪除

• ‘all’ : If all values are NA, drop that row or column.

• ‘all’: 全部都NA,才刪除該列(欄)

thresh : int, optional

Require that many non-NA values. Cannot be combined with how.

(threshold 門檻)

非空元素最低数量。int型，默认为None。

如果该行/列中，非空元素数量小于这个值，就删除该行/列。

subset column label or sequence of labels, optional

Labels along other axis to consider, e.g. if you are dropping rows these would be a list of columns to include.

inplace bool, default False

Whether to modify the DataFrame rather than creating a new one.

inplace：是否原地替换。布尔值，默认为False

 

直接將csv檔讀進來DataFrame: 

原DataFrame有

[13 rows x 7 columns]

其中2 rows , 1 column 為空(NaN)

程式碼: 

import pandas as pd
fpath = r”C:\antenna_AMS\21046\emt2csv\01\01test.csv”
df = pd.read_csv(fpath)

#df = pd.read_csv(fpath,header=None) ;

# 讀取無欄標籤的檔案,自動加0,1,2…當欄標籤

df_drop0 = df.dropna(axis=0, how=’all’)
#先drop空列,axis=0

df_drop1 = df_drop0.dropna(axis=1,how=’all’)
#再drop空欄,axis=1

df_drop0 = df.dropna(axis=0, how=’all’)

[11 rows x 7 columns]

刪除了兩空列

 

df_drop1 = df_drop0.dropna(axis=1,how=’all’)

對df_drop0再drop空欄(axis=1)

[11 rows x 6 columns]

刪除了一個空欄

 

刪除空列會導致index不連續

可以用.reset_index(drop=True) 處理

推薦hahow線上學習python: https://igrape.net/30afN