<p dir="auto"><a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="14542236" data-permission-text="Title is private" data-url="https://github.com/pandas-dev/pandas/issues/3662" data-hovercard-type="issue" data-hovercard-url="/pandas-dev/pandas/issues/3662/hovercard" href="https://github.com/pandas-dev/pandas/issues/3662">#3662</a> is about merging a single-level index with a mi</p>
<p dir="auto">This is is about a multi-multi merge</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="# example described there:
In [11]: df = pd.DataFrame(np.random.randn(10,5))
    ...: df1 = df[range(0, 3)].set_index([0, 2])
    ...: df2 = df[range(2, 5)].set_index([2, 4])
    ...: res = df1.join(df2, how='inner')  # empty. Do I need to specify something here?
    ...: exp = pd.DataFrame({1: df[1], 3: df[3]})
    ...: exp.index = df[2]"><pre class="notranslate"><code class="notranslate"># example described there:
In [11]: df = pd.DataFrame(np.random.randn(10,5))
    ...: df1 = df[range(0, 3)].set_index([0, 2])
    ...: df2 = df[range(2, 5)].set_index([2, 4])
    ...: res = df1.join(df2, how='inner')  # empty. Do I need to specify something here?
    ...: exp = pd.DataFrame({1: df[1], 3: df[3]})
    ...: exp.index = df[2]
</code></pre></div>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="from io import StringIO
csv = r&quot;&quot;&quot;Physical\Flows.Solve,9,1,4,0,0,0,0,0,0
1,2,3,4,5,6,7,8,9,10
&quot;&quot;&quot;
csv = StringIO(csv)
pd.read_csv(csv, engine='python')"><pre class="notranslate"><span class="pl-k">from</span> <span class="pl-s1">io</span> <span class="pl-k">import</span> <span class="pl-v">StringIO</span>
<span class="pl-s1">csv</span> <span class="pl-c1">=</span> <span class="pl-s">r"""Physical\Flows.Solve,9,1,4,0,0,0,0,0,0</span>
<span class="pl-s">1,2,3,4,5,6,7,8,9,10</span>
<span class="pl-s">"""</span>
<span class="pl-s1">csv</span> <span class="pl-c1">=</span> <span class="pl-v">StringIO</span>(<span class="pl-s1">csv</span>)
<span class="pl-s1">pd</span>.<span class="pl-en">read_csv</span>(<span class="pl-s1">csv</span>, <span class="pl-s1">engine</span><span class="pl-c1">=</span><span class="pl-s">'python'</span>)</pre></div>
<p dir="auto">Results in:<br>
<a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/881019/35954774-5cd523e6-0cd7-11e8-80b2-9a15efed3a73.png"><img src="https://user-images.githubusercontent.com/881019/35954774-5cd523e6-0cd7-11e8-80b2-9a15efed3a73.png" alt="image" style="max-width: 100%;"></a></p>
<h4 dir="auto">Problem description</h4>
<p dir="auto">As can be seen the integer zeros have been cast to non-zero floats!</p>
<h4 dir="auto">Output of <code class="notranslate">pd.show_versions()</code></h4>
<details>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0
pytest: 3.3.0
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.27.3
numpy: 1.13.3
scipy: 1.0.0
pyarrow: 0.8.0
xarray: 0.10.0
IPython: 6.2.1
sphinx: 1.6.7
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: 1.5.1
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.5.0b1
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: 1.1.13
pymysql: 0.8.0
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None"><pre class="notranslate"><code class="notranslate">INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0
pytest: 3.3.0
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.27.3
numpy: 1.13.3
scipy: 1.0.0
pyarrow: 0.8.0
xarray: 0.10.0
IPython: 6.2.1
sphinx: 1.6.7
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: 1.5.1
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.5.0b1
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: 1.1.13
pymysql: 0.8.0
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</code></pre></div>
</details>