pandas 合并df错误 [英] Pandas merge df error

问题描述

我要在熊猫中合并3个数据框.一列为20列，另两列各为2列.它们的组织方式如下:

I have 3 dataframes I am trying to merge in pandas. One is 20 columns, the other two have 2 columns each. They are organized as such:

eth_price.head(n=3)

Out[6]: 
            time  eth_price
0  8/28/17 16:19    344.021
2  8/28/17 16:24    343.833
3  8/28/17 16:29    343.643
btc_price.head(n=3)

Out[7]: 
                  time   btc_price
0  2017-08-27 22:50:00  4,389.6113
1  2017-08-27 22:51:00  4,389.0850
2  2017-08-27 22:52:00  4,388.8625

block_data.head(n=3)
Out[8]: 
                   time  block_size    difficulty  estimated_btc_sent  \
0   2017-08-30 22:55:03   165261989  888171856257      22433058065308   
5   2017-08-30 23:02:03   165261989  888171856257      22433058065308   
12  2017-08-30 23:09:03   164262692  888171856257      22210602766312   

    estimated_transaction_volume_usd     hash_rate  market_price_usd  \
0                       1.030796e+09  7.417412e+09           4594.98   
5                       1.030796e+09  7.417412e+09           4594.98   
12                      1.020574e+09  7.373261e+09           4594.98   

    miners_revenue_btc  miners_revenue_usd  minutes_between_blocks  \
0                 2495         11467926.77                    7.98   
5                 2495         11467926.77                    7.98   
12                2478         11388475.85                    8.01   

    n_blocks_mined  n_blocks_total   n_btc_mined    n_tx  nextretarget  \
0              168          482713  210000000000  273392        483839   
5              168          482713  210000000000  273392        483839   
12             167          482713  208750000000  271638        483839   

     total_btc_sent  total_fees_btc          totalbtc  trade_volume_btc  \
0   164688219250248     39574691936  1653391250000000          44110.58   
5   164688219250248     39574691936  1653391250000000          44110.58   
12  163455939539341     39095614135  1653391250000000          44110.58   

    trade_volume_usd  
0       2.026876e+08  
5       2.026876e+08  
12      2.026876e+08  

我正在尝试使用all_data = pd.merge(btc_price, eth_price, block_data, on = 'time', how = 'outer')进行合并，但是当我这样做时，出现以下错误:

I am trying to merge using all_data = pd.merge(btc_price, eth_price, block_data, on = 'time', how = 'outer') however when I do this I get the following error:

文件"，第1行，在 all_data = pd.merge(btc_price，eth_price，block_data，on ='time'，how ='outer')

File "", line 1, in all_data = pd.merge(btc_price, eth_price, block_data, on = 'time', how = 'outer')

TypeError:merge()为参数如何"获得了多个值

TypeError: merge() got multiple values for argument 'how'

这是什么意思，我该如何解决?

What does this mean and how can I fix it?

最终结果应该是一个包含22列的数据帧，包括来自所有3 df的所有行.然后，我将删除缺少值的行.

The end result should be one data frame with 22 columns, including all rows from all 3 df. I will then drop the rows with missing values.

编辑:如果您查看时间戳记，则前2个df发生在分钟，而第3个df发生在03秒...是否可以解决此问题?我有一个脚本，每分钟都会从json中提取这3个文件，我正在尝试相应地对齐3个df

EDIT: if you look at the timestamps, the first 2 df occur on the minute whereas the third occurs at 03 seconds...is there a way of fixing this? I have a script that pulls these 3 files from json every minute and I am trying to align the 3 df accordingly

推荐答案

pd.merge只能合并两个数据帧.第三个参数(在您的情况下为block_data)被解释为如何".您还提供了名为how='outer'的名称，这就是为什么您看到错误消息的原因.解决问题的方法:合并前两个DataFrame，然后将结果与第三个合并.

pd.merge can merge only two DataFrames. The third parameter (block_data in your case) is interpreted as "how." You also supply the named how='outer', and that's why you see the error message. Solution to your problem: merge the first two DataFrames, then merge the result with the third one.

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