Statement of Completion#a703ab06
Namig Akhundov has successfully completed this project.
Intro to Pandas for Data Analysis
easy
DataFrames practice: working with English Words
Resolution
Activities
Project.ipynb
In [20]:
import pandas as pd
In [21]:
df = pd.read_csv('words.csv', index_col='Word')
In [22]:
df.head()
Out[22]:
| Char Count | Value | |
|---|---|---|
| Word | ||
| aa | 2 | 2 |
| aah | 3 | 10 |
| aahed | 5 | 19 |
| aahing | 6 | 40 |
| aahs | 4 | 29 |
Activities¶
How many elements does this dataframe have?¶
In [23]:
print(df.count())
Char Count 172821 Value 172821 dtype: int64
What is the value of the word microspectrophotometries?¶
In [25]:
df.loc["microspectrophotometries"]
Out[25]:
Char Count 24 Value 317 Name: microspectrophotometries, dtype: int64
What is the highest possible value of a word?¶
In [26]:
df["Value"].max()
Out[26]:
319
Which of the following words have a Char Count of 15?¶
In [29]:
words=["pinfish", "microbrew", "superheterodyne", "enfold", "glowing"]
for word in words:
if len(word)==15:
print(word)
superheterodyne
What is the highest possible length of a word?¶
In [30]:
df["Char Count"].max()
Out[30]:
28
What is the word with the value of 319?¶
In [38]:
df[df["Value"]==319]
Out[38]:
| Char Count | Value | |
|---|---|---|
| Word | ||
| reinstitutionalizations | 23 | 319 |
What is the most common value?¶
In [43]:
df["Value"].value_counts().head()
Out[43]:
Value 93 1965 100 1921 95 1915 99 1907 92 1902 Name: count, dtype: int64
What is the shortest word with value 274?¶
In [45]:
df_specval = df[df["Value"]==274]
df_specval.sort_values("Char Count", ascending=True)
Out[45]:
| Char Count | Value | |
|---|---|---|
| Word | ||
| overprotectivenesses | 20 | 274 |
| countercountermeasure | 21 | 274 |
| psychophysiologically | 21 | 274 |
Create a column Ratio which represents the 'Value Ratio' of a word¶
In [50]:
df.insert(2,"Ratio",df["Value"]/df["Char Count"])
df
Out[50]:
| Char Count | Value | Ratio | |
|---|---|---|---|
| Word | |||
| aa | 2 | 2 | 1.000000 |
| aah | 3 | 10 | 3.333333 |
| aahed | 5 | 19 | 3.800000 |
| aahing | 6 | 40 | 6.666667 |
| aahs | 4 | 29 | 7.250000 |
| ... | ... | ... | ... |
| zymotic | 7 | 111 | 15.857143 |
| zymurgies | 9 | 143 | 15.888889 |
| zymurgy | 7 | 135 | 19.285714 |
| zyzzyva | 7 | 151 | 21.571429 |
| zyzzyvas | 8 | 170 | 21.250000 |
172821 rows × 3 columns
What is the maximum value of Ratio?¶
In [52]:
df["Ratio"].describe()
Out[52]:
count 172821.000000 mean 11.825114 std 2.205677 min 1.000000 25% 10.400000 50% 11.875000 75% 13.285714 max 22.500000 Name: Ratio, dtype: float64
What word is the one with the highest Ratio?¶
In [54]:
df[df["Ratio"]==df["Ratio"].max()]
Out[54]:
| Char Count | Value | Ratio | |
|---|---|---|---|
| Word | |||
| xu | 2 | 45 | 22.5 |
How many words have a Ratio of 10?¶
In [57]:
df[df["Ratio"]==10].count()
Out[57]:
Char Count 2604 Value 2604 Ratio 2604 dtype: int64
What is the maximum Value of all the words with a Ratio of 10?¶
In [59]:
df[df["Ratio"]==10].sort_values("Value",ascending=False)
Out[59]:
| Char Count | Value | Ratio | |
|---|---|---|---|
| Word | |||
| electrocardiographically | 24 | 240 | 10.0 |
| electroencephalographies | 24 | 240 | 10.0 |
| electroencephalographer | 23 | 230 | 10.0 |
| electrodesiccation | 18 | 180 | 10.0 |
| phonocardiographic | 18 | 180 | 10.0 |
| ... | ... | ... | ... |
| col | 3 | 30 | 10.0 |
| bis | 3 | 30 | 10.0 |
| sib | 3 | 30 | 10.0 |
| as | 2 | 20 | 10.0 |
| oe | 2 | 20 | 10.0 |
2604 rows × 3 columns
Of those words with a Value of 260, what is the lowest Char Count found?¶
In [64]:
df[df["Value"]==260].sort_values("Char Count", ascending=True)
Out[64]:
| Char Count | Value | Ratio | |
|---|---|---|---|
| Word | |||
| hydroxytryptamine | 17 | 260 | 15.294118 |
| neuropsychologists | 18 | 260 | 14.444444 |
| psychophysiologist | 18 | 260 | 14.444444 |
| revolutionarinesses | 19 | 260 | 13.684211 |
| countermobilizations | 20 | 260 | 13.000000 |
| underrepresentations | 20 | 260 | 13.000000 |
Based on the previous task, what word is it?¶
In [66]:
df.loc[df["Value"]==260, "Char Count"].min()
Out[66]:
17
In [67]:
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) /tmp/ipykernel_17/738365183.py in ?() ----> 1 df.loc[df["Char Count"]==17 & df["Value"]==260, "Word"] /usr/local/lib/python3.11/site-packages/pandas/core/generic.py in ?(self) 1575 @final 1576 def __nonzero__(self) -> NoReturn: -> 1577 raise ValueError( 1578 f"The truth value of a {type(self).__name__} is ambiguous. " 1579 "Use a.empty, a.bool(), a.item(), a.any() or a.all()." 1580 ) ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
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