pandas 熊猫合并df错误
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/46008957/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Pandas merge df error
提问by zsad512
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:
我有 3 个数据框，我想在 Pandas 中合并。一个是 20 列，另外两个各有 2 列。它们的组织方式如下：
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
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:
我正在尝试使用合并，all_data = pd.merge(btc_price, eth_price, block_data, on = 'time', how = 'outer')但是当我这样做时，我收到以下错误：
File "", line 1, in all_data = pd.merge(btc_price, eth_price, block_data, on = 'time', how = 'outer')
TypeError: merge() got multiple values for argument 'how'
文件 "", line 1, in all_data = pd.merge(btc_price, eth_price, block_data, on = 'time', how = 'outer')
类型错误：merge() 为参数“how”获得了多个值
What does this mean and how can I fix it?
这是什么意思，我该如何解决？
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.
最终结果应该是一个包含 22 列的数据框，包括来自所有 3 df 的所有行。然后我将删除缺少值的行。
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
编辑：如果您查看时间戳，前 2 个 df 发生在一分钟，而第三个 df 发生在 03 秒......有没有办法解决这个问题？我有一个脚本每分钟从 json 中提取这 3 个文件，我正在尝试相应地对齐 3 df
回答by DYZ
pd.mergecan merge only twoDataFrames. The third parameter (block_datain 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.
pd.merge只能合并两个DataFrame。第三个参数（block_data在您的情况下）被解释为“如何”。您还提供了 named how='outer'，这就是您看到错误消息的原因。解决您的问题：合并前两个DataFrame，然后将结果与第三个合并。
