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本文小編為大家詳細(xì)介紹“Pandas怎么將表格的前幾行生成html”,內(nèi)容詳細(xì),步驟清晰,細(xì)節(jié)處理妥當(dāng),希望這篇“Pandas怎么將表格的前幾行生成html”文章能幫助大家解決疑惑,下面跟著小編的思路慢慢深入,一起來(lái)學(xué)習(xí)新知識(shí)吧。
import numpy as np import pandas as pd np.random.seed(66) s1 = pd.Series(np.random.rand(20)) s2 = pd.Series(np.random.randn(20)) df = pd.concat([s1, s2], axis=1) df.columns = ['col1', 'col2'] # df.head 取前5行 print(df.head(5).to_html())
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>col1</th>
<th>col2</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0.154288</td>
<td>-0.180981</td>
</tr>
<tr>
<th>1</th>
<td>0.133700</td>
<td>-0.056043</td>
</tr>
<tr>
<th>2</th>
<td>0.362685</td>
<td>-0.185062</td>
</tr>
<tr>
<th>3</th>
<td>0.679109</td>
<td>-0.610935</td>
</tr>
<tr>
<th>4</th>
<td>0.194450</td>
<td>-0.048804</td>
</tr>
</tbody>
</table>
import numpy as np import pandas as pd np.random.seed(66) s1 = pd.Series(np.random.rand(20)) s2 = pd.Series(np.random.randn(20)) df = pd.concat([s1, s2], axis=1) df.columns = ['col1', 'col2'] #median直接算中位數(shù) print(df["col2"].median()) #用50%分位數(shù) print(df["col2"].quantile())
-0.2076894596485453
-0.2076894596485453
iimport numpy as np import pandas as pd np.random.seed(66) s1 = pd.Series(np.random.rand(20)) s2 = pd.Series(np.random.randn(20)) #合并兩個(gè)Series到DF df = pd.concat([s1, s2], axis=1) df.columns = ['col1', 'col2'] # 取最大的五個(gè)數(shù) print(df["col2"].nlargest(5)) print() # 取最小的五個(gè)數(shù) print(df["col2"].nsmallest(5))
12 1.607623
17 1.404255
19 0.675887
13 0.345030
Name: col2, dtype: float6416 -1.220877
18 -1.215324
11 -1.003714
8 -0.936607
5 -0.632613
Name: col2, dtype: float64
""" Churn:客戶是否流失 Yes -> 1 No -> 0 實(shí)現(xiàn)字符串到數(shù)字的映射 """ import pandas as pd df = pd.read_csv("Telco-Customer-Churn.csv") #返回取值,及其取值多少次 print(df["Churn"].value_counts()) df["Churn"] = df["Churn"].map({"Yes": 1, "No": 0}) print() print(df["Churn"].value_counts()) print(df.describe(include=["category"]))
No 5174
Yes 1869
Name: Churn, dtype: int640 5174
1 1869
Name: Churn, dtype: int6
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