title: Pandas Dataframe filter results with Merge. Encoding Decoding Issues
body: <p>I read tons of posts from our database for the last few days. with my limited skills in python and pandas and numpy, i am not sure if i found the answers that I desire. so would you please take a look at my situation, and see what i can do with it. and I am sorry about the chinese characters in the searching results.</p>
  
  <p>I am currently writing some quant analysis for personal use. I retrieved a csv file via tushare-pro, which is a 3825-rows dataframe. </p>
  
  <pre><code>df1 = pd.DataFrame(pd.read_csv(stock_stats_ts.csv))
  data1 = np.array(df1.loc[:,:])
  
  </code></pre>
  
  <p>returns</p>
  
  <pre><code>[[300826 'N测绘' '建筑工程' ... 41.16 16.85 40171.0]
   [2770 '科迪乳业' '乳制品' ... 21.05 4.38 47133.0]
   [2503 '搜于特' '服饰' ... 8.6 3.08 65664.0]
   ...
   [2260 '*ST德奥' '家用电器' ... 23.08 3.03 24704.0]
   [995 '*ST皇台' '白酒' ... 68.05 -35.24 10275.0]
   [939 '*ST凯迪' '新型电力' ... 10.79 -74.92 79373.0]]
  </code></pre>
  
  <p>and then I narrow it down to things i desire, such as code/name/esp/pb/roe</p>
  
  <pre><code>df2 = df1.loc[:,['code','name','esp','pb','npr']]
  data2 = np.array(df1.loc[:,:])
  </code></pre>
  
  <p>returns</p>
  
  <pre><code>[[300826 'N测绘' 1.08 2.79 16.85]
   [2770 '科迪乳业' 0.03 2.13 4.38]
   [2503 '搜于特' 0.098 2.17 3.08]
   ...
   [2260 '*ST德奥' 0.034 0.0 3.03]
   [995 '*ST皇台' -0.079 0.0 -35.24]
   [939 '*ST凯迪' -0.362 0.0 -74.92]]
  </code></pre>
  
  <p>and I also have a list of stock names which i desire from previous session</p>
  
  <pre><code>df3 = pd.DataFrame(pd.read_csv(candidates.csv))
  data3 = np.array(df3.loc[:,['candidates']])
  </code></pre>
  
  <p>returns</p>
  
  <pre><code>[['维维股份']
   ['ST正源']
   ['美克家居']
   ['*ST金山']
   ['大有能源']
   ['好当家']
   ['贵州茅台']
   ['通策医疗']
   ['杭州解百']
   ['耀皮玻璃']
   ['梅花生物']
   ['金牌厨柜']
   ['继峰股份']
   ['胜利股份']
   ['渝 开 发']
   ['云南白药']
   ['中原环保']
   ['兴蓉环境']
   ['华闻集团']
   ['粤 水 电']
   ['濮耐股份']
   ['*ST东南']
   ['洪涛股份']
   ['达实智能']
   ['千红制药']
   ['闽发铝业']
   ['史丹利']
   ['加加食品']
   ['张家港行']
   ['国联水产']]
  </code></pre>
  
  <p>What i am sure of is that my candidates are in df2[name] columns for sure, and then, with what lines of codes so that I can filter my df2 based on the results i have from df3?</p>
  
  <p>Thanks to chief @Rexhil Regmi and @nimrodm, my question worked perfectly with <code>pd.merge</code>. However, all those chinese characters in are encoding in 'gbk' which is unreadable with MS Excel. Any hints to change them into 'utf8'?</p>