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POremoving NaN values in python pandas
 

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  1. POremoving NaN values in python pandas
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    <p>Data is of income of adults from census data, rows look like:</p> <pre><code>31, Private, 84154, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 38, NaN, &gt;50K 48, Self-emp-not-inc, 265477, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, &lt;=50K </code></pre> <p>I'm trying to remove all rows with NaNs from a DataFrame loaded from a CSV file in pandas.</p> <pre><code>&gt;&gt;&gt; import pandas as pd &gt;&gt;&gt; income = pd.read_csv('income.data') &gt;&gt;&gt; income['type'].unique() array([ State-gov, Self-emp-not-inc, Private, Federal-gov, Local-gov, NaN, Self-emp-inc, Without-pay, Never-worked], dtype=object) &gt;&gt;&gt; income.dropna(how='any') # should drop all rows with NaNs &gt;&gt;&gt; income['type'].unique() array([ State-gov, Self-emp-not-inc, Private, Federal-gov, Local-gov, NaN, Self-emp-inc, Without-pay, Never-worked], dtype=object) Self-emp-inc, nan], dtype=object) # what?? &gt;&gt;&gt; income = income.dropna(how='any') # ok, maybe reassignment will work? &gt;&gt;&gt; income['type'].unique() array([ State-gov, Self-emp-not-inc, Private, Federal-gov, Local-gov, NaN, Self-emp-inc, Without-pay, Never-worked], dtype=object) # what?? </code></pre> <p>I tried with a smaller <code>example.csv</code>:</p> <pre><code>label,age,sex 1,43,M -1,NaN,F 1,65,NaN </code></pre> <p>And <code>dropna()</code> worked just fine here for both categorical and numerical NaNs. What is going on? I'm new to Pandas, just learning the ropes. </p>
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    1. USlollercoaster
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      1. VTUpMod
    1. COTry assigning the line `income.dropna(how='any')` to a variable and check the values on that. `dropna()` is not inplace by default (I think the inplace option may have been added after .12).
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      1. USTomAugspurger
    2. CO@TomAugspurger: No also doesn't work.
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      1. USlollercoaster
    3. COTried ```df.dropna(thresh = 1)``` ? More info about your data would be good..
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      1. USdorvak
 

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