(add):分析dalao和修改require_python.txt

require_python.txt

@@ -14,4 +14,4 @@ pipreqs . --encoding=utf8 --force
 
 根据依赖安装包
 
- pip install -r requriements.txt
+ pip install -r requirements.txt

src/code/2003_check_dalao_tokens_ispump.py

@@ -58,6 +58,7 @@ for str_dalaoaddress in arr_str_dalaoaddress:
         dalao_df["ispump"] = 0
         dalao_df["isnengen"] = -1
         
+        dalao_df["beizhu"] = -1
   
         dalao_df["url"] = dalao_df.apply(lambda ser: ( f"https://dexscreener.com/solana/{ser['tokenaddress']}?maker={str_dalaoaddress}"), axis=1)
 

src/code/2004_gmgn_handle_ori_pnl.py

@@ -50,6 +50,10 @@ def get_ana_data_lastdays( df,    intervaldays=30):
         lastdf['profit_usd'] / lastdf['buy_usd'],
         -10,
     )
+    earn_per_neg100_neg30 = len( lastdf[lastdf["earn_percent"] >=-1 & lastdf["earn_percent"] <=-0.3] )
+    earn_per_neg30_pos0 = len( lastdf[lastdf["earn_percent"] >-0.3 & lastdf["earn_percent"] <=0] )
+    earn_per_pos0_pos100 = len( lastdf[lastdf["earn_percent"] >0 & lastdf["earn_percent"] <=1] )
+    earn_per_pos100_posmax = len( lastdf[lastdf["earn_percent"] >1 ] )
     
     earnmain_max = lastdf['profit_usd'].max()
     last_earn_difmax_sum = last_earn_sum - earnmain_max
@@ -58,6 +62,8 @@ def get_ana_data_lastdays( df,    intervaldays=30):
     last_dif_earnper = (
         last_earn_difmax_sum / last_cost_difmax_sum if last_cost_difmax_sum != 0 else -10
     )
+    
+    
     return (
         last_cost_sum,
         last_earn_sum,
@@ -68,6 +74,10 @@ def get_ana_data_lastdays( df,    intervaldays=30):
         last_cost_median,
         last_cost_mean,
         last_trans_amount,
+        earn_per_neg100_neg30,
+        earn_per_neg30_pos0,
+        earn_per_pos0_pos100,
+        earn_per_pos100_posmax,
  
     )
 
@@ -124,8 +134,8 @@ def main():
         (last_07d_cost, last_07d_earn, last_07d_earnper, last_07d_difcost, last_07d_difearn, last_07d_difper, 
         last_07d_costmedian, last_07d_costmean,    last_07d_trans ,   ) = get_ana_data_lastdays( df=cur_df, intervaldays=7)
         
-        (last_15d_cost, last_15d_earn, last_15d_earnper, last_15d_difcost, last_15d_difearn, last_15d_difper, 
-        last_15d_costmedian, last_15d_costmean,    last_15d_trans ,   ) = get_ana_data_lastdays( df=cur_df, intervaldays=15)
+        # (last_15d_cost, last_15d_earn, last_15d_earnper, last_15d_difcost, last_15d_difearn, last_15d_difper, 
+        # last_15d_costmedian, last_15d_costmean,    last_15d_trans ,   ) = get_ana_data_lastdays( df=cur_df, intervaldays=15)
         
         (last_30d_cost, last_30d_earn, last_30d_earnper, last_30d_difcost, last_30d_difearn, last_30d_difper, 
         last_30d_costmedian, last_30d_costmean,    last_30d_trans ,   ) = get_ana_data_lastdays( df=cur_df, intervaldays=30)
@@ -146,15 +156,7 @@ def main():
             last_07d_trans,
     
 
-            last_15d_cost,
-            last_15d_earn,
-            last_15d_earnper,
-            last_15d_difcost,
-            last_15d_difearn,
-            last_15d_difper,
-            last_15d_costmedian,
-            last_15d_costmean,
-            last_15d_trans,
+
 
             last_30d_cost,
             last_30d_earn,
@@ -189,18 +191,6 @@ TotalAnalysis_columns = [
     "07d_costmedian",
     "07d_costmean",
     "07d_trans",
-
-
-    "15d_cost",
-    "15d_earn",
-    "15d_earnper",
-    "15d_difcost",
-    "15d_difearn",
-    "15d_difper",
-    "15d_costmedian",
-    "15d_costmean",
-    "15d_trans",
-
  
     "30d_cost",
     "30d_earn",