pandas df 排序 按列选取

#    mlist = np.arange(0, math.ceil(max_eqMag), 0.1) 

 

# df_b = df_b[df_b['eq_count']>0]
# print(df_b)
## df_b.sort_values("m",inplace=True,ascending=False)
#
# df_b['sum_count'] = df_b['eq_count'].cumsum()
## df_b = df_b[df_b['sum_count']>1]

序列排序 按索引，按值排序

s.sort_index()

s.sort_values()

遍历pd.Series的index和value的方法

for i, v in s.items():
print('index: ', i, 'value: ', v)
#index: a value: 1
#index: b value: 2
#index: c value: 3
#index: d value: 4

for i, v in s.iteritems():
print('index: ', i, 'value: ', v)
#index: a value: 1
#index: b value: 2
#index: c value: 3
#index: d value: 4

 

 

 

1. import pandas as pd
2.  
    
3.  
   dict=[[1,2,3,4,5,6],[0,0,0,0,0,0]]
4.  
   data=pd.DataFrame(dict)
5.  
   print(data)
6.  
   for indexs in data.index:
7.  
   print(data.loc[indexs].values[0:-1])

( 按行遍历数据)

1.  
   import pandas as pd
2.  
    
3.  
   dict=[[1,2,3,4,5,6],[0,0,0,0,0,0]]
4.  
   data=pd.DataFrame(dict)
5.  
   print(data)
6.  
   for indexs in data.columns:
7.  
   print(data[indexs])

(按列遍历数据)

 

 

for row in d_new.iterrows():
　　# print(row[1]['t_d'])

　　Nu.append(d_new[d_new['t_d']>=row[1]['t_d']].count())